Foundations and Trends® in Computer Graphics and Vision
Local velocity-adapted motion events for spatio-temporal recognition
Computer Vision and Image Understanding
Human Motion Characterization Using Spatio-temporal Features
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Motion segmentation using an occlusion detector
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Local feature trajectories for efficient event-based indexing of video sequences
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Local descriptors for spatio-temporal recognition
SCVMA'04 Proceedings of the First international conference on Spatial Coherence for Visual Motion Analysis
A survey of video datasets for human action and activity recognition
Computer Vision and Image Understanding
Application of 3D-wavelet statistics to video analysis
Multimedia Tools and Applications
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The notion of local features in space-time has recently been proposed to capture and describe local events in video. When computing space-time descriptors, however, the result may strongly depend on the relative motion between the object and the camera. To compensate for this variation, we present a method that automatically adapts the features to the local velocity of the image pattern and, hence, results in a video representation that is stable with respect to different amounts of camera motion. Experimentally we show that the use of velocity adaptation substantially increases the repeatability of interest points as well as the stability of their associated descriptors. Moreover, for an application to human action recognition we demonstrate how velocity-adapted features enable recognition of human actions in situations with unknown camera motion and complex, non-stationary backgrounds.