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This paper presents an approach for human activity recognition by representing the frames of the video sequence with the distribution of local motion features and their spatiotemporal arrangements. In this approach, the local motion features used for the representation of a frame are integrated from the ones detected in this frame and its temporal neighbors. The featurespsila spatial arrangements...
This paper presents a spatiotemporal pyramid representation for recognizing facial expressions and hand gestures. This approach works by partitioning video sequence into increasingly fine subdivisions in the space and time domains and modeling the distribution of the local motion features inside each subdivision such that the set of motion features are mapped into spatial and temporal multi-resolution...
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