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Vassilis Athitsos

Name

[Athitsos, Vassilis]
  • Professor, Department of Computer Science & Engineering
  • University of Texas at Arlington

Biography

Vassilis Athitsos received the BS degree in mathematics from the University of Chicago in 1995, the MS degree in computer science from the University of Chicago in 1997, and the PhD degree in computer science from Boston University in 2006. In 2005-2006 he worked as a researcher at Siemens Corporate Research, developing methods for database-guided medical image analysis. In 2006-2007 he was a postdoctoral research associate at the Computer Science department at Boston University. In August 2007 he joined the Computer Science and Engineering department at the University of Texas at Arlington, where he currently serves as full professor. His research interests include computer vision, machine learning, and data mining. His recent work has focused on gesture and sign language recognition, detection and tracking of humans using computer vision, efficient similarity-based retrieval in multimedia databases, shape modeling and detection, and medical image analysis. His research has been supported by the National Science Foundation, including an NSF CAREER award.

Professional Preparation

    • 2006 Ph.D. in Computer ScienceBoston University
    • 1997 M.S. in Computer ScienceUniversity of Chicago
    • 1995 B.S. in Mathematics (Computer Science),  University of Chicago

Appointments

    • Sept 2018 to Present Full Professor
      Department of Computer Science and Engineering   University of Texas at Arlington
    • Sept 2012 to Aug 2018 Assoc Prof
      University of Texas at Arlington
    • Sept 2007 to Aug 2012 Assist Professor
      University of Texas at Arlington
    • Oct 2006 to Aug 2007 Postdoc
      Boston University
    • Aug 2005 to Sept 2006 Researcher
      Siemens Corporate Research

News Articles

Research and Expertise

  • Vassilis Athitsos
    My main research areas are computer vision, machine learning, and data mining. At UTA, I have established the VLM research lab. A large part of my current work focuses on developing general methods for efficient and accurate similarity-based retrieval and classification, with applications in sign language recognition, content-based access in image, video and multimedia databases, and recognition of objects and shapes. Please refer to my web page and my publications for more details.

Publications

      Conference Paper 2017
      • Varun Kanal, Maher Abujelala, Srujana Gattupalli, Vassilis Athitsos, and Fillia Makedon.
        APSEN: Pre-Screening Tool for Sleep Apnea in a Home Environment.
        International Conference on Human-Computer Interaction (HCI International), July 2017.

        {Conference Paper }
      2017
      • Srujana Gattupalli, Dylan Ebert, Michalis Papakostas, Fillia Makedon, and Vassilis Athitsos.
        CogniLearn: A Deep Learning-based Interface for Cognitive Behavior Assessment.
        ACM Conference on Intelligent User Interfaces (IUI), March 2017.

        {Conference Paper }
      2017
      • Amir Ghaderi, Srujana Gattupalli, Dylan Ebert, Ali Sharifara, Vassilis Athitsos, and Fillia Makedon.
        Improving the Accuracy of the CogniLearn System for Cognitive Behavior Assessment.
        Pervasive Technologies Related to Assistive Environments (PETRA), June 2017.

        {Conference Paper }
      2017
      • Alex Dillhoff, Himanshu Pahwa, Christopher Conly, and Vassilis Athitsos.
        Providing Meaningful Alignments for Periodic Signs.
        Pervasive Technologies Related to Assistive Environments (PETRA), June 2017.

        {Conference Paper }
      2017
      • Radu Tudor Ionescu, Marius Popescu, Christopher Conly, and Vassilis Athitsos.
        Local Frame Match Distance: A Novel Approach for Exemplar Gesture Recognition.
        European Signal Processing Conference (EUSIPCO), August 2017.

        {Conference Paper }
      2017
      • Sakher Ghanem, Christopher Conly, and Vassilis Athitsos.
        A Survey on Sign Language Recognition Using Smartphones.
        Pervasive Technologies Related to Assistive Environments (PETRA), June 2017.

        {Conference Paper }

      Journal Article 2017
      • Hugo Jair Escalante, Isabelle Guyon, Vassilis Athitsos, Pat Jangyodsuk, and Jun Wan.
        Principal Motion Components for One-Shot Gesture Recognition. 
        Journal on Pattern Analysis and Applications, 20(1), pages 167-182, February 2017.

        {Journal Article }

      Conference Paper 2016
      • Manish Annappa, Sharma Chakravarthy, and Vassilis Athitsos.
        Pre-processing of Video Streams for Extracting Queryable Representation of Its Contents.
        International Symposium on Visual Computing (ISVC), December 2016.

        {Conference Paper }
      2016
      • Christopher Conly, Alex Dillhoff, and Vassilis Athitsos.
        Leveraging Intra-Class Variations to Improve Large Vocabulary Gesture Recognition.
        International Conference on Pattern Recognition (ICPR), December 2016.

        {Conference Paper }
      2016
      • Amir Ghaderi and Vassilis Athitsos.
        Selective Unsupervised Feature Learning with Convolutional Neural Network (S-CNN).
        International Conference on Pattern Recognition (ICPR), December 2016.

        {Conference Paper }
      2016
      • Srujana Gattupalli, Alexandros Lioulemes, Shawn N. Gieser, Paul Sassaman, Vassilis Athitsos, and Fillia Makedon.
        MAGNI: A Real-time Robot-assisted Game-based Tele-Rehabilitation System.
        International Conference on Human-Computer Interaction, August 2016.

        {Conference Paper }
      2016
      • Srujana Gattupalli, Amir Ghaderi, and Vassilis Athitsos.
        Evaluation of Deep Learning based Pose Estimation for Sign Language.
        Pervasive Technologies Related to Assistive Environments (PETRA), June 2016.

        {Conference Paper }

      Journal Article 2016
      • Sergio Escalera, Vassilis Athitsos, and Isabelle Guyon.
        Challenges in Multimodal Gesture Recognition.
        Journal of Machine Learning Research (JMLR), 17(72), pages 1-54, June 2016.

        {Journal Article }
      2016
      • Alexios Kotsifakos, Vassilis Athitsos, and Panagiotis Papapetrou.
        Query-sensitive Distance Measure Selection for Time Series Nearest Neighbor Classification 
        International Journal of Intelligent Data Analysis (IDA), 20(1), pages 5-27, January 2016.

        {Journal Article }

      Conference Paper 2015
      • Wei Xiang, Christopher Conly, Christopher McMurrough and Vassilis Athitsos.
        A Review and Quantitative Comparison of Methods for Kinect Calibration. 
        International Workshop on Sensor-based Activity Recognition and Interaction (iWOAR), June 2015.

        {Conference Paper }
      2015
      • Christopher Conly, Zhong Zhang, and Vassilis Athitsos.
        An integrated RGB-D system for looking up the meaning of signs. 
        Pervasive Technologies Related to Assistive Environments (PETRA), July 2015.

        {Conference Paper }
      2015
      • Zhong Zhang, Christopher Conly, and Vassilis Athitsos.
        A survey on vision-based fall detection. 
        Pervasive Technologies Related to Assistive Environments (PETRA), July 2015.

        {Conference Paper }
      2015
      • Pat Jangyodsuk, Panagiotis Papapetrou, and Vassilis Athitsos.
        Optimizing Hashing Functions for Similarity Indexing in Arbitrary Metric and Nonmetric Spaces 
        SIAM International Conference on Data Mining (SDM), May 2015.

        {Conference Paper }
      2015
      • Soheil Shafiee, Farhad Kamangar, and Vassilis Athitsos.
        A Multi-Modal Sparse Coding Classifier Using Dictionaries with Different Number of Atoms. 
        IEEE Winter Conference on Applications of Computer Vision (WACV), January 2015.

        {Conference Paper }

      Journal Article 2015
      • Alexios Kotsifakos, Isak Karlsson, Panagiotis Papapetrou, Vassilis Athitsos, and Dimitrios Gunopulos.
        Embedding-based Subsequence Matching with Gaps-Range- Tolerances: a Query-By-Humming application 
        Very Large Databases Journal (VLDBJ), 24(4), pages 519-536, August 2015.

        {Journal Article }
      2015
      • Alexios Kotsifakos, Alexandra Stefan, Vassilis Athitsos, Gautam Das, and Panagiotis Papapetrou.
        DRESS: Dimensionality Reduction for Efficient Sequence Search 
        Data Mining and Knowledge Discovery Journal (DAMI), 29(5), pages 1280-1311, September 2015.

        {Journal Article }

      Conference Paper 2014
      • Zhong Zhang, Christopher Conly, and Vassilis Athitsos.
        Evaluating Depth-Based Computer Vision Methods for Fall Detection Under Occlusions. 
        International Symposium on Visual Computing (ISVC), December 2014.

        {Conference Paper }
      2014
      • Soheil Shafiee, Farhad Kamangar, Vassilis Athitsos, Junzhou Huang, and Laleh Ghandehari.
        Multimodal Sparse Representation Classification with Fisher Discriminative Sample Reduction. 
        IEEE International Conference on Image Processing (ICIP), October 2014.

        {Conference Paper }
      2014
      • Zhong Zhang, Christopher Conly, and Vassilis Athitsos.
        Hand Detection on Sign Language Videos. 
        Pervasive Technologies Related to Assistive Environments (PETRA), May 2014.

        {Conference Paper }
      2014
      • Pat Jangyodsuk, Christopher Conly, and Vassilis Athitsos.
        Sign Language Recognition using Dynamic Time Warping and Hand Shape Distance Based on Histogram of Oriented Gradient Features. 
        Pervasive Technologies Related to Assistive Environments (PETRA), May 2014.

        {Conference Paper }
      2014
      • Christopher Conly, Zhong Zhang, and Vassilis Athitsos.
        An Evaluation of RGB-D Skeleton Tracking for Use in Large Vocabulary Complex Gesture Recognition. 
        Pervasive Technologies Related to Assistive Environments (PETRA), May 2014.

        {Conference Paper }
      2014
      • Dimitrios Zikos, Konstantinos Tsiakas, Fadiah Qudah, Vassilis Athitsos, and Fillia Makedon.
        Evaluation of Classification Methods for the Prediction of Hospital Length of Stay using Medicare Claims Data. 
        Pervasive Technologies Related to Assistive Environments (PETRA), May 2014.

        {Conference Paper }

      Journal Article 2014
      • Isabelle Guyon, Vassilis Athitsos, Pat Jangyodsuk, Hugo Jair Escalante, Ben Hamner.
        The ChaLearn Gesture Dataset (CGD 2011). 
        Journal of Machine Vision and Applications, 25(8), 1929-1951, November 2014.

        {Journal Article }
      2014
      • Jun Wan, Vassilis Athitsos, Pat Jangyodsuk, Hugo Jair Escalante, Qiuqi Ruan, Isabelle Guyon.
        CSMMI: Class-Specific Maximization of Mutual Information for Action and Gesture Recognition. 
        IEEE Transactions on Image Processing, 23(7), 3152-3165, July 2014.

        {Journal Article }
      2014
      • Vangelis Metsis, Dimitrios Kosmopoulos, Vassilis Athitsos, and Fillia Makedon. 
        Non-Invasive Analysis of Sleep Patterns via Multimodal Sensor Input.
        Journal of Personal and Ubiquitous Computing, 18(1), 19-26, January 2014. 

        {Journal Article }

      Conference Paper 2013
      • Sergio Escalera, Jordi Gonzàlez, Xavier Baró, Miguel Reyes, Isabelle Guyon, Vassilis Athitsos, Hugo Jair Escalante, Leonid Sigal, Antonis Argyros, Cristian Sminchisescu, Richard Bowden, and Stan Sclaroff.
        ChaLearn multi-modal gesture recognition 2013: grand challenge and workshop summary. 
        Chalearn Multi-Modal Gesture Recognition Workshop, International Conference on Multimodal Interaction, ICMI, December 2013.

        {Conference Paper }
      2013
      • Sergio Escalera, Jordi Gonzàlez, Xavier Baró, Miguel Reyes, Oscar Lopés, Isabelle Guyon, Vassilis Athitsos, and Hugo J. Escalante.
        Multi-modal Gesture Recognition Challenge 2013: Dataset and Results. 
        Chalearn Multi-Modal Gesture Recognition Workshop, International Conference on Multimodal Interaction, ICMI, December 2013.

        {Conference Paper }
      2013
      • Pat Jangyodsuk and Vassilis Athitsos.
        An Indexing Method for Efficient Model-Based Search. 
        International Conference on Image Processing, Computer Vision, and Pattern Recognition, July 2013.

        {Conference Paper }
      2013
      • Soheil Shafiee, Farhad Kamangar, Vassilis Athitsos, and Junzhou Huang.
        Efficient Sparse Representation Using Adaptive Clustering. 
        International Conference on Image Processing, Computer Vision, and Pattern Recognition, July 2013.

        {Conference Paper }
      2013
      • Christopher Conly, Paul Doliotis, Pat Jangyodsuk, Rommel Alonzo, and Vassilis Athitsos.
        Toward a 3D Body Part Detection Video Dataset and Hand Tracking Benchmark. 
        Pervasive Technologies Related to Assistive Environments (PETRA), May 2013.

        {Conference Paper }
      2013
      • Alexios Kotsifakos, Evangelos E. Kotsifakos, Panagiotis Papapetrou, and Vassilis Athitsos.
        Genre Classification of Symbolic Music with SMBGT. 
        Conference on Pervasive Technologies Related to Assistive Environments (PETRA), May 2013.

        {Conference Paper }
      2013
      • Soheil Shafiee, Farhad Kamangar, and Vassilis Athitsos.
        The Role of Dictionary Learning in Sparse Representation-based Classification for Face Recognition. 
        Conference on Pervasive Technologies Related to Assistive Environments (PETRA), May 2013.

        {Conference Paper }
      2013
      • Vangelis Metsis, Pat Jangyodsuk, Vassilis Athitsos, Maura Iversen, and Fillia Makedon.
        Computer Aided Rehabilitation for Patients with Rheumatoid Arthritis. 
        Cyber-Physical Systems (CPS) workshop, January 2013. 

        {Conference Paper }
      2013
      • Alexios Kotsifakos, Panagiotis Papapetrou, and Vassilis Athitsos. 
        IBSM: Interval-Based Sequence Matching. 
        SIAM International Conference on Data Mining (SDM), May 2013.

        {Conference Paper }

      Journal Article 2013
      • Alexandra Stefan, Vassilis Athitsos, and Gautam Das. 
        The Move-Split-Merge Metric for Time Series.
        IEEE Transactions on Knowledge and Data Engineering (TKDE), 25(6), pages 1425-1438, June 2013. 

        {Journal Article }

      Journal Article 2012
      • Haohan Zhu, George Kollios, and Vassilis Athitsos. "A Generic Framework for Efficient and Effective Subsequence Retrieval." Proceedings of the VLDB Endowment (PVLDB), 5(11), pages 1579-1590, July 2012.
        {Journal Article }
      2012
      • Kevin Dela Rosa, Vangelis Metsis, and Vassilis Athitsos."Boosted Ranking Models: A Unifying Framework for Ranking Predictions," International Journal of Knowledge and Information Systems (KAIS), 30(3), pages 543-568, March 2012.
        {Journal Article }

      Conference Paper 2012
      • Isabelle Guyon, Vassilis Athitsos, Pat Jangyodsuk, Ben Hamner, and Hugo Jair Escalante. "ChaLearn Gesture Challenge: Design and First Results." Workshop on Gesture Recognition and Kinect Demonstration Competition, June 2012.

        {Conference Paper }
      2012
      • Zhong Zhang, Weihua Liu, Vangelis Metsis, and Vassilis Athitsos. "A Viewpoint-Independent Statistical Method for Fall Detection." International Conference on Pattern Recognition (ICPR), November 2012.

        {Conference Paper }
      2012
      • Alexios Kotsifakos, Panagiotis Papapetrou, Jaakko Hollmén, Dimitrios Gunopulos, Vassilis Athitsos, and George Kollios. "Hum-a-song: A Subsequence Matching with Gaps-Range-Tolerances Query-By-Humming System." International Conference on Very Large Databases (VLDB) demo paper, August 2012.

        {Conference Paper }
      2012
      • Paul Doliotis, Vassilis Athitsos, Dimitrios Kosmopoulos, and Stavros Perantonis. "Hand Shape and 3D Pose Estimation using Depth Data from a Single Cluttered Frame." International Symposium on Visual Computing (ISVC), July 2012.

        {Conference Paper }
      2012
      • Alexios Kotsifakos, Panagiotis Papapetrou, Jaakko Hollmén, Dimitrios Gunopulos, and Vassilis Athitsos. "A Survey of Query-By-Humming Similarity Methods." Conference on Pervasive Technologies Related to Assistive Environments (PETRA), June 2012.

        {Conference Paper }
      2012
      • Christopher McMurrough, Christopher Conly, Vassilis Athitsos, and Fillia Makedon. "3D Point of Gaze Estimation Using Head-Mounted RGB-D Cameras." Proceedings of the 14th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS), October 2012.

        {Exhibition Review }

      Conference Paper 2011
      • Alexios Kotsifakos, Vassilis Athitsos, Panagiotis Papapetrou, Jaakko Hollmén, Dimitrios Gunopulos. "Model-Based Search in Large Time Series Databases," Conference on Pervasive Technologies Related to Assistive Environments (PETRA), June 2011.
        {Conference Paper }
      2011
      • Paul Doliotis, Alexandra Stefan, Chris Mcmurrough, David Eckhard, Vassilis Athitsos. "Comparing Gesture Recognition Accuracy Using Color and Depth Information," Conference on Pervasive Technologies Related to Assistive Environments (PETRA), June 2011.
        {Conference Paper }
      2011
      • Joshua Davies, Farhad Kamangar, Gergely Zaruba, Manfred Huber, Vassilis Athitsos. "Use of RSSI and Time-of-Flight Wireless Signal Characteristics for Location Tracking," Conference on Pervasive Technologies Related to Assistive Environments (PETRA), June 2011.
        {Conference Paper }
      2011
      • ZhongZhang, Rommel Alonzo, Vassilis Athitsos. "Experiments with Computer Vision Methods for Hand Detection," Conference on Pervasive Technologies Related to Assistive Environments (PETRA), June 2011.
        {Conference Paper }
      2011
      • Isabelle Guyon and Vassilis Athitsos. "Demonstrations and Live Evaluation for the Gesture Recognition Challenge."IEEE International Workshop on Human-Computer Interaction, November 2011.

        {Conference Paper }

      Journal Article 2011
      • Panagiotis Papapetrou, Vassilis Athitsos, Michalis Potamias, George Kollios, and Dimitrios Gunopulos."Embedding-based Subsequence Matching in Time Series Databases." ACM Transactions on Database Systems (TODS), 36(3), Article 17, 2011.
        {Journal Article }

      Journal Article 2010
      • Vassilis Athitsos, Haijing Wang, and Alexandra Stefan. "A Database-Based Framework for Gesture Recognition," Journal of Personal and Ubiquitous Computing, 14(6), pages 511-526, September 2010.
        {Journal Article }

      Conference Paper 2010
      • C. N. Athitsos, J. N. Sclaroff, A. T. Stefan, H. Wang, and Q. Yuan. "Large Lexicon Project: American Sign Language Video Corpus and Sign Language Indexing/Retrieval Algorithms," in Workshop on the Representation and Processing of Sign Languages: Corpora and Sign Language Technologies (CSLT) (Valletta, Malta, 2010), pp. 11-14.
        {Conference Paper }
      2010
      • E. B. Zhang, R. Arora, and V. Athitsos. "Experiments with com- puter vision methods for fall detection," in Conference on Pervasive Technologies Related to Assistive Environments (PETRA) (Samos, Greece, 2010).
        {Conference Paper }
      2010
      • P. P. Lijffijt, J. Hollmen, and V. Athitsos. "Benchmarking dynamic time warping for music retrieval," in Workshop on Multimedia Event Analysis for Assistive Environments (Samos, Greece, 2010).
        {Conference Paper }
      2010
      • A. S. Wang, V. A. Moradi, C. Neidle, and F. Kamangar. "A System for Large Vocabulary Sign Search," in Workshop on Sign, Gesture and Activity (SGA) (Heraclion, Greece, 2010).
        {Conference Paper }

      Conference Paper 2009
      • H. Wang, A. Stefan, and V. Athitsos. "A Similarity Measure for Vision-Based Sign Recognition," in International Conference on Universal Access in Human-Computer Interaction (UAHCI) (San Diego, CA, 2009), pp. 607-616.
        {Conference Paper }
      2009
      • A. Stefan, V. Athitsos, Q. Yuan, and S. Sclaroff. "Reducing JointBoost-Based Multiclass Classification to Proximity Search," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Miami, Florida, USA, 2009), pp. 589-596.
        {Conference Paper }
      2009
      • A. Stefan, H. Wang, and V. Athitsos. "Towards Automated Large Vocabulary Gesture Search," in ACM Conference on Pervasive Technologies Related to Assistive Environments (PETRA) (Corfu, Greece, 2009).
        {Conference Paper }
      2009
      • P. Papapetrou, P. Doliotis, and V. Athitsos. "Towards Faster Activity Search Using Embedding-Based Subsequence Matching," in Workshop on Multimedia Event Analysis for Assistive Environments (Corfu, Greece, 2009).
        {Conference Paper }
      2009
      • P. Doliotis, G. Tsekouras, C. N. Anagnostopoulos, and V. Athitsos. "Intelligent Modification of Colors in Digitized Paintings for Enhancing the Visual Perception of Color-blind Viewers," in IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI) (2009).
        {Conference Paper }

      Journal Article 2009
      • P. Papapetrou, V. Athitsos, G. Kollios, and D. Gunopulos. "Reference-Based Alignment in Large Sequence Databases," Proceedings of the VLDB Endowment, vol. 2, no. 1, pp. 205-216, 2009.
        {Journal Article }
      2009
      • J. Alon, V. Athitsos, Q. Yuan, and S. Sclaroff. "A Unified Framework for Gesture Recognition and Spatiotemporal Gesture Segmentation," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 31, no. 9, pp. 1685-1699, September 2009.
        {Journal Article }

      Conference Paper 2008
      • V. Athitsos, P. Papapetrou, M. Potamias, G. Kollios, and D. Gunopulos. "Approximate Embedding-Based Subsequence Matching of Time Series," in ACM International Conference on Management of Data (SIGMOD) (Vancouver, British Columbia, Canada, 2008), pp. 365-378.
        {Conference Paper }
      2008
      • P. Dreuw, C. Neidle, V. Athitsos, S. Sclaroff, and H. Ney. "Benchmark Databases for Video-Based Automatic Sign Language Recognition," in International Conference on Language Resources and Evaluation (LREC) (Marrakech, Morocco, 2008), pp. 1115-1120.
        {Conference Paper }
      2008
      • V. Athitsos, M. Potamias, P. Papapetrou, and G. Kollios. "Nearest Neighbor Retrieval Using Distance-Based Hashing," in IEEE International Conference on Data Engineering (ICDE) (Cancun, Mexico, 2008), pp. 327-336.
        {Conference Paper }
      2008
      • Z. Wu, M. Betke, J. Wang, V. Athitsos, and S. Sclaroff. "Tracking with Dynamic Hidden State Shape Models," in European Conference on Computer Vision (ECCV) (Marseille, France, 2008), pp. 643-656.
        {Conference Paper }
      2008
      • M. Potamias and V. Athitsos. "Nearest neighbor search methods for handshape recognition," in ACM Conference on Pervasive Technologies Related to Assistive Environments (PETRA) (Athens, Greece, 2008).
        {Conference Paper }
      2008
      • A. Stefan, V. Athitsos, J. Alon, and S. Sclaroff. "Translation and Scale-Invariant Gesture Recognition in Complex Scenes," in ACM Conference on Pervasive Technologies Related to Assistive Environments (PETRA) (Athens, Greece, 2008).
        {Conference Paper }
      2008
      • C. N. Athitsos, J. N. Sclaroff, Q. Y. Stefan, and A. Thangali. "The American Sign Language Lexicon Video Dataset," in IEEE Workshop on Computer Vision and Pattern Recognition for Human Communicative Behavior Analysis (CVPR4HB) (Anchorage, Alaska, USA, 2008).
        {Conference Paper }

      Journal Article 2008
      • J. Wang, V. Athitsos, S. Sclaroff, and M. Betke. "Detecting Objects of Variable Shape Structure With Hidden State Shape Models," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 30, no. 3, pp. 477-492, March 2008.
        {Journal Article }
      2008
      • V. Athitsos, J. Alon, S. Sclaroff, and G. Kollios. "BoostMap: An Embedding Method for Efficient Nearest Neighbor Retrieval," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 30, no. 1, pp. 89-104, January 2008.
        {Journal Article }

      Conference Paper 2007
      • V. Athitsos, A. Stefan, Q. Yuan, and S. Sclaroff. "ClassMap: Efficient Multiclass Recognition via Embeddings," in IEEE International Conference on Computer Vision (ICCV) (Rio de Janeiro, Brazil, 2007).
        {Conference Paper }
      2007
      • A. Barbu, V. Athitsos, B. Georgescu, S. Boehm, P. Durlak, and D. Comaniciu. "Hierarchical Learning of Curves: Application to Guidewire Localization in Fluoroscopy," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Minneapolis, Minnesota, USA, 2007).
        {Conference Paper }

      Journal Article 2007
      • V. Athitsos, M. Hadjieleftheriou, G. Kollios, and S. Sclaroff. "Query-Sensitive Embeddings," ACM Transactions on Database Systems (TODS), vol. 32, no. 2, June 2007.
        {Journal Article }

      Conference Paper 2006
      • V. Athitsos, J. Wang, S. Sclaroff, and M. Betke. "Detecting Instances of Shape Classes That Exhibit Variable Structure," in European Conference on Computer Vision (ECCV) (Graz, Austria, 2006), pp. 121-134.
        {Conference Paper }

      Book Chapter 2006
      • V. Athitsos, J. Alon, S. Sclaroff, and G. Kollios. "Learning Embeddings for Fast Approximate Nearest Neighbor Retrieval," Nearest-Neighbor Methods in Learning and Vision, Theory and Practice, G. Shakhnarovich, T. Darrell, and P. Indyk, Eds. MIT Press, 2006, pp. 143-161.
        {Book Chapter }

      Conference Paper 2005
      • M. Vlachos, Z. Vagena, P. S. Yu, and V. Athitsos. "Rotation Invariant Indexing of Shapes and Line Drawings," in ACM Conference on Information and Knowledge Management (CIKM) (Bremen, Germany, 2005), pp. 131-138.
        {Conference Paper }
      2005
      • J. Alon, V. Athitsos, and S. Sclaroff. "Accurate and Efficient Gesture Spotting via Pruning and Subgesture Reasoning," in IEEE Workshop on Human Computer Interaction (Beijing, China, 2005), pp. 189-198.
        {Conference Paper }
      2005
      • Alon, J., Athitsos, V., & Sclaroff, S. (2005). Online and Offline Character Recognition Using Alignment to Prototypes. In International Conference on Document Analysis and Recognition (ICDAR) (pp. 839-843). Seoul, Korea:.
        {Conference Paper }
      2005
      • Sclaroff, S., Betke, M., Kollios, G., Alon, J., Athitsos, V., Li, R., & Magee, J. (2005). Tracking, Analysis, and Recognition of Human Gestures in Video. In International Conference on Document Analysis and Recognition (ICDAR) (pp. 806-810). Seoul, Korea:.
        {Conference Paper }
      2005
      • V. Athitsos, M. Hadjieleftheriou, G. Kollios, and S. Sclaroff. "Query-Sensitive Embeddings," in ACM International Conference on Management of Data (SIGMOD) (Baltimore, Maryland, USA, 2005), pp. 706-717.
        {Conference Paper }
      2005
      • V. Athitsos, J. Alon, and S. Sclaroff. "Efficient Nearest Neighbor Classification Using a Cascade of Approximate Similarity Measures.," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (San Diego, California, USA, 2005), pp. 486-493.
        {Conference Paper }
      2005
      • V. Athitsos and S. Sclaroff. "Boosting Nearest Neighbor Classifiers for Multiclass Recognition," in IEEE Workshop on Learning in Computer Vision and Pattern Recognition (San Diego, California, USA, 2005).
        {Conference Paper }
      2005
      • J. A. Athitsos, S. Sclaroff, and G. Kollios. "Filtering Methods for Similarity-Based Multimedia Retrieval," in Seventh International Workshop of the EU Network of Excellence DELOS on Audio-Visual Content and Information Visualization in Digital Libraries (Cortona, Italy, 2005).
        {Conference Paper }
      2005
      • J. Alon, V. Athitsos, Q. Yuan, and S. Sclaroff. "Simultaneous Localization and Recognition of Dynamic Hand Gestures," in IEEE Motion Workshop (Breckenridge, Colorado, USA, 2005), pp. 254-260.
        {Conference Paper }
      2005
      • Q. Yuan, S. Sclaroff, and V. Athitsos. "Automatic 2D Hand Tracking in Video Sequences," in IEEE Workshop on Applications of Computer Vision (Breckenridge, Colorado, USA, 2005), pp. 250-256.
        {Conference Paper }

      Conference Paper 2004
      • V. Athitsos, J. Alon, S. Sclaroff, and G. Kollios. "BoostMap: A Method for Efficient Approximate Similarity Rankings," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Washington, DC, USA, 2004), pp. 268-275.
        {Conference Paper }

      Journal Article 2004
      • L. Sigal, S. Sclaroff, and V. Athitsos. "Skin Color-Based Video Segmentation under Time-Varying Illumination," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 26, no. 7, pp. 862-877, July 2004.
        {Journal Article }

      Conference Paper 2003
      • V. Athitsos and S. Sclaroff. "Estimating 3D Hand Pose from a Cluttered Image," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Madison, Wisconsin, USA, 2003), pp. 432-439.
        {Conference Paper }
      2003
      • V. Athitsos and S. Sclaroff. "Database Indexing Methods for 3D Hand Pose Estimation," in Gesture Workshop (Genova, Italy, 2003), pp. 288-299.
        {Conference Paper }

      Conference Paper 2002
      • V. Athitsos and S. Sclaroff. "An Appearance-Based Framework for 3D Hand Shape Classification and Camera Viewpoint Estimation," in IEEE Conference on Automatic Face and Gesture Recognition (Washington, DC, USA, 2002), pp. 45-52.
        {Conference Paper }

      Conference Paper 2001
      • V. Athitsos and S. Sclaroff. "3D Hand Pose Estimation by Finding Appearance-Based Matches in a Large Database of Training Views," in IEEE Workshop on Cues in Communication (Lihue, Hawaii, USA, 2001).
        {Conference Paper }
      2001
      • R. Rosales, V. Athitsos, L. Sigal, and S. Sclaroff. "3D Hand Pose Reconstruction Using Specialized Mappings," in IEEE International Conference on Computer Vision (ICCV) (Vancouver, British Columbia, Canada, 2001), pp. 378-385.
        {Conference Paper }

      Journal Article 2001
      • C. Neidle, S. Sclaroff, and V. Athitsos. "SignStream: A Tool for Linguistic and Computer Vision Research on Visual-Gestural Language Data," Behavior Research Methods, Instruments and Computers, vol. 33, no. 3, pp. 311-320, August 2001.
        {Journal Article }

      Book Chapter 2001
      • V. Athitsos, C. Frankel, and M. J. Swain. "Integrating Analysis of Context and Image Content," Principles of Visual Information Retrieval, M. S. Lew, Eds. Springer-Verlag, 2001, pp. 279-296.
        {Book Chapter }

      Journal Article 2000
      • M. LaCascia, S. Sclaroff, and V. Athitsos. "Fast, Reliable Head Tracking under Varying Illumination: An Approach Based on Robust Registration of Texture-Mapped 3D Model," IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 22, no. 4, pp. 322-336, April 2000.
        {Journal Article }

      Conference Paper 2000
      • L. Sigal, S. Sclaroff, and V. Athitsos. "Estimation and Prediction of Evolving Color Distributions for Skin Segmentation Under Varying Illumination," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (Hilton Head, South Carolina, USA, 2000), pp. 2152-2159.
        {Conference Paper }

      Conference Paper 1997
      • V. Athitsos, M. J. Swain, and C. Frankel. "Distinguishing Photographs and Graphics on the World Wide Web," in IEEE Workshop on Content-Based Access of Image and Video Libraries (San Juan, Puerto Rico, 1997), pp. 10-17.
        {Conference Paper }

      Technical Report 1996
      • Frankel, C., Swain, M., & Athitsos, V. (1996). WebSeer: An Image Search Engine for the World Wide Web. University of Chicago Department of Computer Science Technical Report TR-96-14.
        {Technical Report }

Support & Funding

This data is entered manually by the author of the profile and may duplicate data in the Sponsored Projects section.
    • Oct 2016 to Sept 2020 CHS: Large: Collaborative Research: Computational Science for Improving Assessment of Executive Function in Children sponsored by  - $1291495
    • May 2016 to Apr 2017 Workshop: Doctoral Consortium at the PETRA 2016 Conference sponsored by  - $27580
    • Sept 2017 to Aug 2020 PFI:BIC: iWork, a Modular Multi-Sensing Adaptive Robot-Based Service for Vocational Assessment, Personalized Worker Training and Rehabilitation sponsored by  - $615803
    • Aug 2017 to June 2018 Evaluation of Face Detection and Face Recognition Algorithms sponsored by  - $59463
    • Oct 2013 to Sept 2018 MRI Collaborative: Development of iRehab, an intelligent closed-loop instrument for adaptive rehabilitation sponsored by  - $847890
    • Sept 2014 to Aug 2017 CI-P: Planning for SMART-MOVE: A Spatiotemporal Annotated Human Activity Repository for Advanced Motion Recognition and Analysis Research sponsored by  - $116000
    • Apr 2011 to Mar 2016 CAREER: Large Vocabulary Gesture Recognition for Everyone: Gesture Modeling and Recognition Tools for System Builders and Users sponsored by  - $651563
    • Aug 2011 to July 2015 Collaborative: II-EN: Development of Publicly Available, Easily Searchable, Linguistically Analyzed, Video Corpora for Sign Language and Gesture Research sponsored by  - $98630
    • Sept 2011 to Aug 2012 Collaborative: Gesture Recognition Challenge sponsored by  - $55920
    • Aug 2012 to Aug 2015 GAANN - Educating Health Informatics Researchers at the Computer Science and Engineering Department of the University of Texas at Arlington sponsored by  - $533064
    • Sept 2010 to Aug 2014 CPS: Medium: A Novel Human Centric CPS to Improve Motor/Cognitive Assessment and Enable Adaptive Rehabilitation sponsored by  - $714001
    • Oct 2009 to Sept 2012 MRI: Development of a Next-Generation Multimodal Data Management Human-Sensing Instrument for Trustworthy Research Collaboration and Quality of Life Improvement sponsored by  - $770622
    • Sept 2008 to Aug 2012 III-COR-Small: Collaborative Research: Time Series Subsequence Matching for Content-based Access in Very Large Multimedia Databases sponsored by  - $281001
    • Sept 2007 to Aug 2011 Large Lexicon Gesture Representation, Recognition, and Retrieval sponsored by  - $208968

Patents

    • Nov 2011 8050482  System and method for online optimization of guidewire visibility in fluoroscopic systems

      A method for online optimization of guidewire visibility in fluoroscopic images includes providing an digitized image acquired from a fluoroscopic imaging system, the image comprising an array of intensities corresponding to a 2-dimensional grid of pixels, detecting a guidewire in the fluoroscopic image, enhancing the visibility of the guidewire in the fluoroscopic image, calculating a visibility measure of the guidewire in the fluoroscopic image, and readjusting acquisition parameters of the fluoroscopic imaging system wherein the guidewire visibility is improved.

    • June 2011 7970171  System and method for simultaneously subsampling fluoroscopic images and enhancing guidewire visibility

      A method for downsampling fluoroscopic images and enhancing guidewire visibility during coronary angioplasty includes providing a first digitized image, filtering the image with one or more steerable filters of different angular orientations, assigning a weight W and orientation O for each pixel based on the filter response for each pixel, wherein each pixel weight is assigned to a function of a maximum filter response magnitude and the pixel orientation is calculated from the angle producing the maximum filter response if the magnitude is greater than zero, wherein guidewire pixels have a higher weight than non-guidewire pixels, and downsampling the orientation and weights to calculate a second image of half the resolution of the first image, wherein the downsampling accounts for the orientation and higher weight assigned to the guidewire pixels.

    • Sept 2010 7792342  System and method for detecting and tracking a guidewire in a fluoroscopic image sequence

      A system and method for populating a database with a set of image sequences of an object is disclosed. The database is used to detect localization of a guidewire in the object. A set of images of anatomical structures is received in which each image is annotated to show a guidewire, catheter, wire tip and stent. For each given image a Probabilistic Boosting Tree (PBT) is used to detect short line segments of constant length in the image. Two segment curves are constructed from the short line segments. A discriminative joint shape and appearance model is used to classify each two segment curve. A shape of an n-segment curve is constructed by concatenating all the two segment curves. A guidewire curve model is identified that includes a start point, end point and the n-segment curve. The guidewire curve model is stored in the database.

Students Supervised

Courses

      • CSE 4310-001 Introduction to Computer Vision

        This course introduces students to basic concepts and techniques in computer vision. The topics covered include moprhological operations, connected component analysis, image filters, edge detection, feature extraction, object detection, object recognition, tracking, gesture recognition, image formation and camera models, calibration, and stereo vision. A strong programming background is assumed, as well as familiarity with linear algebra (vector and matrix operations), and knowledge of basic probability theory and statistics. Prerequisites for CSE 4310: Admitted into an Engineering Professional Program, and C or better in each of the following: CSE 2320, IE 3301, and either CSE 3380 or MATH 3330.

        Spring - Regular Academic Session - 2019 Download Syllabus Contact info & Office Hours
      • CSE 5392-003 Introduction to Computer Vision

        This course introduces students to basic concepts and techniques in computer vision. The topics covered include moprhological operations, connected component analysis, image filters, edge detection, feature extraction, object detection, object recognition, tracking, gesture recognition, image formation and camera models, calibration, and stereo vision. A strong programming background is assumed, as well as familiarity with linear algebra (vector and matrix operations), and knowledge of basic probability theory and statistics. Prerequisites for CSE 4310: Admitted into an Engineering Professional Program, and C or better in each of the following: CSE 2320, IE 3301, and either CSE 3380 or MATH 3330.

        Spring - Regular Academic Session - 2019 Download Syllabus Contact info & Office Hours
      • CSE 4309-001 Introduction to Machine Learning

        This course offers an introduction to machine learning. Topics include naive Bayes classifiers, linear regression, linear classificiers, neural networks and backpropagation, kernel methods, decision trees, clustering, and reinforcement learning. A strong programming background is assumed, as well as familiarity with linear algebra (vector and matrix operations), and knowledge of basic probability theory and statistics.

        Fall - Regular Academic Session - 2018 Download Syllabus Contact info & Office Hours
      • CSE 4309-001 Introduction to Machine Learning

        This course offers an introduction to machine learning. Topics include naive Bayes classifiers, linear regression, linear classificiers, neural networks and backpropagation, kernel methods, decision trees, clustering, and reinforcement learning. A strong programming background is assumed, as well as familiarity with linear algebra (vector and matrix operations), and knowledge of basic probability theory and statistics.

        Fall - Regular Academic Session - 2017 Download Syllabus Contact info & Office Hours1 Link
      • CSE 6363-001 MACHINE LEARNING

        A detailed investigation of current machine learning methods, including statistical, connectionist, and symbolic learning. Presents theoretical results for comparing methods and determining what is learnable. Current issues in machine learning research will also be examined.

        Spring - Regular Academic Session - 2017 Download Syllabus Contact info & Office Hours1 Link
      • CSE 1310-006 Introduction to Computers and Programming

        This course introduces students to computers, to the algorithmic process, and to programming using basic control and data structures. The programming language used in this course is Java.

        Fall - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • CSE 4308-001 Artificial Intelligence

        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods, probabilistic reasoning, and machine learning.

        Fall - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • CSE 1310-003 INTRODUCTION TO COMPUTERS AND PROGRAMMING

        This course introduces students to computers, to the algorithmic process, and to programming using basic control and data structures. The programming language used in this course is Java.

        Spring - Regular Academic Session - 2016 Download Syllabus Contact info & Office Hours
      • CSE 1310-006 Introduction to Computers and Programming

        This course introduces students to computers, to the algorithmic process, and to programming using basic control and data structures. The programming language used in this course is Java.

        Fall - Regular Academic Session - 2015 Download Syllabus Contact info & Office Hours
      • CSE 4308-001 Artificial Intelligence

        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods, probabilistic reasoning, and machine learning.

        Fall - Regular Academic Session - 2015 Download Syllabus Contact info & Office Hours
      • CSE 1310-001 Introduction to Computers and Programming

        This course introduces students to computers, to the algorithmic process, and to programming using basic control and data structures. The programming language used in this course is Java.

      • CSE 4308-001 ARTIFICIAL INTELLIGENCE I

        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Graphplan), probabilistic reasoning, and machine learning.

      • CSE 5360-001 ARTIFICIAL INTELLIGENCE I

        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Graphplan), probabilistic reasoning, and machine learning.

      • CSE 1310-004 Introduction to Computers and Programming

        This course introduces students to computers, to the algorithmic process, and to programming using basic control and data structures. The programming language used in this course is Python.

        Spring - Regular Academic Session - 2015 Download Syllabus Contact info & Office Hours1 Link
      • CSE 2312-001 Computer Organization and Assembly Language Programming

        Computer organization from the viewpoint of software, including: the memory hierarchy, instruction set architectures, memory addressing, input-output, integer and floating-point representation and arithmetic. The relationship of higher-level-programming languages to the operating system and to instruction set architecture are explored. The course also teaches some programming in an assembly language.

      • CSE 2320-001 Algorithms and Data Structures

        This course teaches students how to design, choose, and evaluate appropriate algorithms when designing and implementing software. Students will learn a broad set of algorithms covering different problems, including sorting, search, spanning trees, and network flow. Students will also learn about basic data structures, such as linked lists, stacks, and queues. The course will also teach students basic methods for analyzing algorithmic properties such as time and space complexity.

      • CSE 4317-003 Senior Design II

        The course objective is to learn how to develop real world products, the right way, and also learn a lot about the development life-cycle process and yourself along the way! This is the CSE capstone course, where you put it all together before you tackle the real world. We will study the product development environment used today in the computer industry, and practice the phased system development process as applied to computer hardware and software design projects. You will work for two semesters in teams of students. In CSE 4316 you will prepare and present planning and definition documentation for your design project. The project will be continued and completed by the same team in CSE 4317 the following semester.

        Spring - Regular Academic Session - 2014 Download Syllabus Contact info & Office Hours
      • CSE 6389-001 CSE 6389 - Special Topics in Advanced Multimedia, Graphics, and Image Processing

        This course will engage students in individual, student-designed projects, where students will design and implement advanced computer vision methods. Topics of interest include:

        - detecting and recognizing people in a scene.
        - gesture and sign language recognition.
        - object detection and recognition.
        - camera calibration.

        Students will be graded based on quality of project and quality of presentations.

        Fall - Regular Academic Session - 2013 Download Syllabus Contact info & Office Hours
      • CSE 4316-003 Senior Design I

        The course objective is to learn how to develop real world products, the right way, and also learn a lot about the development life-cycle process and yourself along the way! This is the CSE capstone course, where you put it all together before you tackle the real world. We will study the product development environment used today in the computer industry, and practice the phased system development process as applied to computer hardware and software design projects. You will work for two semesters in teams of students. In CSE 4316 you will prepare and present planning and definition documentation for your design project. The project will be continued and completed by the same team in CSE 4317 the following semester.

        Fall - Regular Academic Session - 2013 Download Syllabus Contact info & Office Hours1 Link
      • CSE 1310-001 Introduction to Computers and Programming

        This course introduces students to computers, to the algorithmic process, and to programming using basic control and data structures. The programming language used in this course is Python.

        Summer - Regular Academic Session - 2013 Download Syllabus Contact info & Office Hours1 Link
      • CSE 4308-001 Artificial Intelligence

        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.

        Summer - Regular Academic Session - 2013 Download Syllabus Contact info & Office Hours1 Link
      • CSE 6389-001 Special Topics: Image and Video Databases
        This course will engage students in individual, student-designed projects, where students will design and implement advanced computer vision methods. Topics of interest include:

        •  detecting and recognizing people in a scene.
        •  detecting and tracking individual body parts such as faces and hands.
        •  model-based and exemplar-based methods for recognizing gestures and signs.
        •  object recognition.
        •  camera calibration.


        Spring - Regular Academic Session - 2013 Download Syllabus 1 Link
      • CSE 4317-003 Senior Design II
        The course objective is to learn how to develop real world products, the right way, and also learn a lot about the development life-cycle process and yourself along the way! This is the CSE capstone course, where you put it all together before you tackle the real world. We will study the product development environment used today in the computer industry, and practice the phased system development process as applied to computer hardware and software design projects. You will work for two semesters in teams of students. In CSE 4316 you will prepare and present planning and definition documentation for your design project. The project will be continued and completed by the same team in CSE 4317 the following semester.
        Spring - Regular Academic Session - 2013 Download Syllabus 1 Link
      • CSE 4316-003 Senior Design I
        The course objective is to learn how to develop real world products, the right way, and also learn a lot about the development life-cycle process and yourself along the way! This is the CSE capstone course, where you put it all together before you tackle the real world. We will study the product development environment used today in the computer industry, and practice the phased system development process as applied to computer hardware and software design projects. You will work for two semesters in teams of students. In CSE 4316 you will prepare and present planning and definition documentation for your design project. The project will be continued and completed by the same team in CSE 4317 the following semester.
        Fall - Regular Academic Session - 2012 Download Syllabus 1 Link
      • CSE 1310-001 Introduction to Computers and Programming
        This course introduces students to computers, to the algorithmic process, and to programming using basic control and data structures. The programming language used in this course is Python.
        Summer - Regular Academic Session - 2012 Download Syllabus 1 Link
      • CSE 5360-001 ARTIFICIAL INTELLIGENCE I
        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.
        Summer - Regular Academic Session - 2012 Download Syllabus 1 Link
      • CSE 6367-001 Computer Vision
        This course introduces students to basic concepts and techniques in computer vision. Students successfully completing this course will be able to apply a variety of computer techniques for the design of efficient algorithms for real-world applications, such as optical character recognition, face detection and recognition, motion estimation, human tracking, and gesture recognition. The topics covered include image formation and camera models, linear filters, edge detection, stereo vision, image segmentation, feature extraction, object detection, object recognition, tracking, image/video databases. The course will be graded based on programming assignments, which must be solved in MATLAB, C, C++, or Java.
        Spring - Regular Academic Session - 2012 Download Syllabus 1 Link
      • CSE 6369-001 Special Topics in Advanced Intelligent Systems: Sign Language Recognition

        This course will engage students in individual, student-designed projects, where students will design computer vision methods for sign language recognition. Topics of interest include:

        • detecting and recognizing people in a scene.
        • detecting and tracking individual body parts such as faces and hands.
        • model-based and exemplar-based methods for recognizing gestures and signs.
        • approaches for visualizing recognition results and the behavior of different system components.
        • defining measures of performance and conducting meaningful quantitative experiments.
        Spring - Regular Academic Session - 2012 Download Syllabus 1 Link
      • CSE 4308-001 Artificial Intelligence
        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.
        Fall - Regular Academic Session - 20111 Link
      • CSE 5360-001 ARTIFICIAL INTELLIGENCE I
        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.
        Fall - Regular Academic Session - 20111 Link
      • CSE 6367-001 Computer Vision
        This course introduces students to basic concepts and techniques in computer vision. Students successfully completing this course will be able to apply a variety of computer techniques for the design of efficient algorithms for real-world applications, such as optical character recognition, face detection and recognition, motion estimation, human tracking, and gesture recognition. The topics covered include image formation and camera models, linear filters, edge detection, stereo vision, image segmentation, feature extraction, object detection, object recognition, tracking, image/video databases. The course will be graded based on programming assignments, which must be solved in MATLAB, C, C++, or Java.
        Spring - Regular Academic Session - 20111 Link
      • CSE 5360-001 ARTIFICIAL INTELLIGENCE I
        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.
        Fall - Regular Academic Session - 20101 Link
      • CSE 4308-001 Artificial Intelligence
        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.
        Fall - Regular Academic Session - 20101 Link
      • CSE 5360-001 ARTIFICIAL INTELLIGENCE I
        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.
        Fall - Regular Academic Session - 20101 Link
      • CSE 6389-001 Special Topics: Image and Video Databases
        The goal of this course is to study methods for comparing and identifying visual patterns. For example, these visual patterns can correspond to letters, hands, gestures, faces, or other types of objects or activities. The first topic we study is: what are meaningful ways to evaluate the similarity between visual patterns? How can we tell that a pattern A is more similar to a pattern B than to a pattern C? The course covers different similarity measures, including correlation, the Euclidean distance, the chamfer distance, the Hausdorff distance, dynamic time warping, the edit distance, and shape context matching. The second topic of this course is: how can we find efficiently the most similar match for a test pattern in a large database of images or video? The course covers different indexing methods, that can efficiently identify the best matches without having to exhaustively compare the test image or video to every database image or video.
        Summer - Regular Academic Session - 2010 Download Syllabus 1 Link
      • CSE 4308-001 Artificial Intelligence
        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.
        Summer - Regular Academic Session - 20101 Link
      • CSE 5360-001 ARTIFICIAL INTELLIGENCE I
        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.
        Summer - Regular Academic Session - 20101 Link
      • CSE 6389-001 Special Topics: Image and Video Databases
        The goal of this course is to study methods for comparing and identifying visual patterns. For example, these visual patterns can correspond to letters, hands, gestures, faces, or other types of objects or activities. The first topic we study is: what are meaningful ways to evaluate the similarity between visual patterns? How can we tell that a pattern A is more similar to a pattern B than to a pattern C? The course covers different similarity measures, including correlation, the Euclidean distance, the chamfer distance, the Hausdorff distance, dynamic time warping, the edit distance, and shape context matching. The second topic of this course is: how can we find efficiently the most similar match for a test pattern in a large database of images or video? The course covers different indexing methods, that can efficiently identify the best matches without having to exhaustively compare the test image or video to every database image or video.
        Summer - Regular Academic Session - 2010 Download Syllabus 1 Link
      • CSE 1311-002 Introductory Programming for Engineers and Scientists
        This course introduces students to the algorithmic process and to programming in C using standard control structures, arrays, files, strings, pointers, bit manipulation and structures.
        Spring - Regular Academic Session - 2010 Download Syllabus 1 Link
      • CSE 6367-001 Computer Vision
        This course introduces students to basic concepts and techniques in computer vision. Students successfully completing this course will be able to apply a variety of computer techniques for the design of efficient algorithms for real-world applications, such as optical character recognition, face detection and recognition, motion estimation, human tracking, and gesture recognition. The topics covered include image formation and camera models, linear filters, edge detection, stereo vision, image segmentation, feature extraction, object detection, object recognition, tracking, image/video databases. The course will be graded based on programming assignments, which must be solved in MATLAB, C, C++, or Java.
        Spring - Regular Academic Session - 20101 Link
      • CSE 4308-001 Artificial Intelligence
        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.
        Fall - Regular Academic Session - 20091 Link
      • CSE 5360-001 ARTIFICIAL INTELLIGENCE I
        This course gives an introduction to the philosophies and techniques of Artificial Intelligence. AI techniques have become an essential element in modern computer software and are thus essential for a successful career and advanced studies in computer science. Students successfully completing this course will be able to apply a variety of techniques for the design of efficient algorithms for complex problems. Topics covered in this course include search algorithms (such as breadth-first, depth-first, A*), game-playing algorithms (such as Minimax), knowledge and logic reasoning, planning methods (such as STRIPS and Partially Ordered Planner), probabilistic reasoning, and machine learning.
        Fall - Regular Academic Session - 20091 Link
      • CSE 4392-003 Computer Vision
        This course introduces students to basic concepts and techniques in computer vision. Students successfully completing this course will be able to apply a variety of computer techniques for the design of efficient algorithms for real-world applications, such as optical character recognition, face detection and recognition, motion estimation, human tracking, and gesture recognition. The topics covered include image formation and camera models, linear filters, edge detection, stereo vision, image segmentation, feature extraction, object detection, object recognition, tracking, image/video databases. The course will be graded based on programming assignments, which must be solved in MATLAB, C, C++, or Java.
        Spring - Regular Academic Session - 2009 Download Syllabus 1 Link
      • CSE 4392-003 Computer Vision
        This course introduces students to basic concepts and techniques in computer vision. Students successfully completing this course will be able to apply a variety of computer techniques for the design of efficient algorithms for real-world applications, such as optical character recognition, face detection and recognition, motion estimation, human tracking, and gesture recognition. The topics covered include image formation and camera models, linear filters, edge detection, stereo vision, image segmentation, feature extraction, object detection, object recognition, tracking, image/video databases. The course will be graded based on programming assignments, which must be solved in MATLAB, C, C++, or Java.
        Spring - Regular Academic Session - 2009 Download Syllabus 1 Link

Service to the Community

  • Appointed
    • Nov 2013 to  Present Associate Editor

      Image and Video Computing Journal

    • Apr 2013 to  Present Area Chair

      IEEE Conference on Automatic Face and Gesture Recognition, 2013, 2017.

    • Jan 2009 to  Present National Science Foundation Review Panelist

      2009, 2010, 2011, 2012, 2013, 2014

    • Jan 2006 to  Present Program committee member or reviewer for conferences

      ICPR 2016, ISVC 2016, ECCV 2016, CVPR 2016, PETRA 2016, ICCV 2015, WACV 2015, PETRA 2015, CVPR 2015,  ISVC 2015, Face and Gesture 2015, ISVC 2014, ECCV 2014, PETRA 2014, ICPR 2014, CVPR 2014, ICDM 2013, ICCV 2013, CIKM 2013, CVPR 2013, PETRA 2013, ISVC 2013, CIKM 2013, ICPR 2012, ECCV 2012, PETRA 2012, ISVC 2012, KDD 2012, ICDM 2011, ECML/PKDD 2011, KDD 2011, PETRA 2011, ICDM 2010, ECCV 2010, CVPR 2010, CIKM 2010, PETRA 2010, ICCV 2009, CVPR 2009, PETRA 2009, PAKDD 2009, CIVR 2009, BIOT 2009, ICDM 2008, CVPR 2008, PETRA 2008, BIOT 2008, ICCV 2007, KDD 2007, CVPR 2007, CVPR 2006, KDD 2006.

    • Jan 2006 to  Present Reviewer for journals

      IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), International Journal of Computer Vision (IJCV), ACM Transactions on Database Systems (TODS), IEEE Transactions on Information Technology in Biomedicine (TITB), IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Transactions on Image Processing (TIP), ACM Transactions on Multimedia Computing, Communications and Applications (TOMCCAP), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE Transactions on Multimedia, IEEE Transactions on Neural Networks (TNN), IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics (SMCB), IEEE Transactions on Information Forensics and Security (TIFS), Pattern Recognition, Pattern Recognition Letters, Computer Vision and Image Understanding (CVIU), Image and Vision Computing (IVC), International Journal of Image and Video Processing (IJIVP), Data Mining and Knowledge Discovery, Annals of Operations Research, Personal and Ubiquitous Computing, Annals of Biomedical Engineering, IEEE Computer Graphics and Applications.

    • Jan 2011 to  Dec 2014 Guest Editor

      Journal of Machine Learning Research, Special Topic on Gesture Recognition

  • Volunteered
    • Jan 2011 to  Dec 2012 Co-organizer

      ICPR 2012 Gesture Recognition Challenge and Kinect Grand Prize

      CVPR 2012 Workshop on Gesture recognition and Kinect Demonstration Competition

      CVPR 2011 Workshop on Gesture Recognition

Service to the University

  • Other
    • Sept 2007 to  Present Department/University Service

      Chair of Faculty Recruiting Committee, 2012-2013.

      Coordinator of all sections of CSE 1310 - Introduction to Computers and Programming, 2014-present.

      Advisor for UTA ICPC Committee and UTA Undergraduate Programming Club, 2007-present.

      Undergraduate Studies Committee, 2013-present.

      Graduate Studies Committee, 2007-present.

      Advisory Committee, 2016-present.

      Adjunct Advising Committee, 2016-present.

      Faculty Recruiting Committee, 2007-2011, 2015-2016.

      Ph.D. Admissions Committee, 2007-2011, 2012-2014.

      Colloquium Committee, 2007-2008.

      Website Review Committee, 2007-2008.

      Volunteer for RoPro High School Programming Competition, 2008, 2009, 2010, 2011.

      Lecturer for UTA Engineering and Computer Science Summer Camps, 2009, 2010.