Riemannian manifold-based support vector machine for human activity classification in images


This paper addresses the issue of classification of human activities in still images. We propose a novel method where part-based features focusing on human and object interaction are utilized for activity representation, and classification is designed on manifolds by exploiting underlying Riemannian geometry. The main contributions of the paper include: (a… (More)
DOI: 10.1109/ICIP.2013.6738715

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