Video-Based Action Recognition Using Rate-Invariant Analysis of Covariance Trajectories

23 Mar 2015Zhengwu ZhangJingyong SuEric KlassenHuiling LeAnuj Srivastava

Statistical classification of actions in videos is mostly performed by extracting relevant features, particularly covariance features, from image frames and studying time series associated with temporal evolutions of these features. A natural mathematical representation of activity videos is in form of parameterized trajectories on the covariance manifold, i.e. the set of symmetric, positive-definite matrices (SPDMs)... (read more)

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