Behavior Recognition Method Based on Joint Statistical Descriptor in Wavelet Domain
A recognition method and wavelet domain technology, applied in the field of video processing, can solve problems such as low feature dimension, unconsidered coefficient direction, relationship between coefficients, insufficient data coverage, etc., to achieve effective extraction and reduce impact
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[0027] Reference figure 1 , The method of behavior recognition based on wavelet domain joint statistical descriptors of the present invention, the steps are as follows:
[0028] Step 1: Densely sample the behavior video to extract the dense trajectory of the video sequence.
[0029] Common trajectory extraction methods include trajectory tracking based on KLT (Kanade-Lucas-Tomasi), trajectory tracking based on SIFT (Scale Invariant Feature Transform) descriptor matching, and trajectory tracking based on dense optical flow. The present invention uses the dense optical flow-based trajectory tracking method proposed by Wang et al. in the article "Action recognition by dense trajectories" in 2011 to extract the motion trajectory of the behavior video, and the steps are as follows:
[0030] (1.1) Use dense grids to densely sample the video in eight scale spaces in turn, and the scaling factor between every two scale spaces is The sampling interval is 5 pixels;
[0031] (1.2) Calculate th...
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