View-Invariant Representations for Human Activity Recognition
The representation plays an important role in recognition and understanding of human action from video sequences. A view-invariant representation of action consisting of dynamic instants and intervals, which is computed using spatiotemporal curvature of a trajectory, is presented. In order to validate our representation, we report experiments on several different actions performed by different people, and captured in different viewpoints.
Cen Rao, Mubarak Shah, and Tanveer Syeda-Mahmood, Action Rectionition based onView Invariant Spatio-temporal Analysis, ACM Multimedia 2003, Nov 2-8, Berkeley, CA USA.
View-invariant Alignment and matching of Video Sequences, The Ninth IEEE International Conference on Computer Vision, ICCV 2003, Nice, France
Cen Rao, Alper Yilmaz, and Mubarak Shah, View-Invariant Representation And Recognition of Actions, International Journal of Computer Vision, Vol. 50, Issue 2, 2002
Cen Rao and Mubarak Shah, View Invariance in Action Recognition, Computer Vision and Pattern Recognition, CVPR 2001, Kauai, Hawaii, Dec 11-13, 2001
Cen Rao and Mubarak Shah, View-Invariant Representation and Learning of Human Action, IEEE Workshop on Detection and Recognition of Events in Video, Vancouver, Canada, July 8, 2001
Cen Rao and Mubarak Shah, A View-Invariant Representation of Human Action, International Conference on Control, Automation, Robotics and Vision, Singapore, Dec 5th-8th, 2000
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