The reliable identification of human activities in video, for example whether a person is walking, clapping, waving, etc. is extremely important for video interpretations. Since different people could perform the same action across different number of frames, matching two different sequences of the same actions is not a trivial task. In this paper we discuss a new technique for video sequence matching where the matched sequences are of different sizes. The proposed technique is based on frequency domain analysis of feature data. The experiments are shown to achieve high recognition accuracy of 95.4% on recognizing 8 different human actions, and out-perform two baseline methods of comparison.
['Jessica JunLin Wang', 'Sameer Singh']
Spatial feature based recognition of human dynamics in video sequences