Segmentation of Discriminative Patches in Human Activity Video

Abstract

In this article, we present a novel approach to segment discriminative patches in human activity videos. First, we adopt the spatio-temporal interest points (STIPs) to represent significant motion patterns in the video sequence. Then, nonnegative sparse coding is exploited to generate a sparse representation of each STIP descriptor. We construct the feature… (More)
DOI: 10.1145/2750780

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@article{Zhang2015SegmentationOD, title={Segmentation of Discriminative Patches in Human Activity Video}, author={Bo Zhang and Nicola Conci and Francesco G. B. De Natale}, journal={TOMCCAP}, year={2015}, volume={12}, pages={4:1-4:19} }