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Human action recognition from video clips has received increasing attention in recent years. This paper proposes a simple yet effective method for the problem of action recognition. The method aims to encode human actions using the quantized vocabulary of averaged silhouettes that are derived from space-time windowed shapes and implicitly capture local temporal motion as well as global body shape...
Existing action recognition approaches mainly rely on the discriminative power of individual local descriptors extracted from spatio-temporal interest points (STIP), while the geometric relationships among the local features are ignored. This paper presents new features, called pairwise features (PWF), which encode both the appearance and the spatio-temporal relations of the local features for action...
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