Parameterized modeling and recognition of activities

A framework for modeling and recognition of temporal activities is proposed. The modeling of sets of exemplar activities is achieved by parameterizing their representation in the form of principal components. Recognition of spatio-temporal variants of modeled activities is achieved by parameterizing the search in the space of admissible transformations that the activities can undergo. Experiments on recognition of articulated and deformable object motion from image motion parameters are presented.

[1]  Michael J. Black,et al.  The Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow Fields , 1996, Comput. Vis. Image Underst..

[2]  Larry S. Davis,et al.  Human expression recognition from motion using a radial basis function network architecture , 1996, IEEE Trans. Neural Networks.

[3]  Mubarak Shah,et al.  VISUALLY RECOGNIZING SPEECH USING EIGENSEQUENCES , 1997 .

[4]  James W. Davis,et al.  An appearance-based representation of action , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[5]  Larry S. Davis,et al.  Recognition of head gestures using hidden Markov models , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[6]  Larry S. Davis,et al.  Towards 3-D model-based tracking and recognition of human movement: a multi-view approach , 1995 .

[7]  David J. Fleet,et al.  Learning parameterized models of image motion , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Thad Starner,et al.  Visual Recognition of American Sign Language Using Hidden Markov Models. , 1995 .

[9]  Edward H. Adelson,et al.  Analyzing and recognizing walking figures in XYT , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[10]  Aaron F. Bobick,et al.  A state-based technique for the summarization and recognition of gesture , 1995, Proceedings of IEEE International Conference on Computer Vision.

[11]  Charles R. Dyer,et al.  Cyclic motion detection using spatiotemporal surfaces and curves , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[12]  Mubarak Shah,et al.  Matching motion trajectories using scale-space , 1993, Pattern Recognit..

[13]  Alex Pentland,et al.  Space-time gestures , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Y. Ariki,et al.  Recognition of Head Gestures Using Hidden Markov Models , 1996 .

[15]  Michael J. Black,et al.  EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation , 1996, ECCV.

[16]  Michael J. Black,et al.  Cardboard people: a parameterized model of articulated image motion , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.