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From Videos to Verbs: Mining Videos for Activities using a Cascade of Dynamical Systems

10 years 1 months ago
From Videos to Verbs: Mining Videos for Activities using a Cascade of Dynamical Systems
Clustering video sequences in order to infer and extract activities from a single video stream is an extremely important problem and has significant potential in video indexing, surveillance, activity discovery and event recognition. Clustering a video sequence into activities requires one to simultaneously recognize activity boundaries (activity consistent subsequences) and cluster these activity subsequences. In order to do this, we build a generative model for activities (in video) using a cascade of dynamical systems and show that this model is able to capture and represent a diverse class of activities. We then derive algorithms to learn the model parameters from a video stream and also show how a single video sequence may be clustered into different clusters where each cluster represents an activity. We also propose a novel technique to build affine, view, rate invariance of the activity into the distance metric for clustering. Experiments show that the clusters found by the alg...
Pavan K. Turaga, Ashok Veeraraghavan, Rama Chellap
Added 12 Oct 2009
Updated 28 Oct 2009
Type Conference
Year 2007
Where CVPR
Authors Pavan K. Turaga, Ashok Veeraraghavan, Rama Chellappa
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