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Much of action recognition research is recently based on a bag of words (BOW) representation by quantizing the extracted 3D interest points from videos. The k-means algorithm is commonly used to construct a visual vocabulary. However, it has two major drawbacks. Firstly, the visual vocabulary is sensitive to the vocabulary size and the initialization. Secondly, k-means is unable to capture the salient...
Sparse representation has been applied recently to many signal processing and computer vision and demonstrated successful results. Inspired by them, we propose an action recognition approach based on sparse representation to avoid the sensitivity of parameter selection in nearest-neighbor classification method and improve the discriminative capability. Firstly, each frame in the test sequence is treated...
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