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AssigneeThe Research Foundation for The State University of New York
InventorsJason J. Corso, Sreemanananth Sadanand
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The present invention is a method for carrying out high-level activity recognition on a wide variety of videos. In one embodiment, the invention leverages the fact that a large number of smaller action detectors, when pooled appropriately, can provide high-level semantically rich features that are superior to low-level features in discriminating videos. Another embodiment recognizes activity using a bank of template objects corresponding to actions and having template sub-vectors. The video is processed to obtain a featurized video and a corresponding vector is calculated. The vector is correlated with each template object sub-vector to obtain a correlation vector. The correlation vectors are computed into a volume, and maximum values are determined corresponding to one or more actions.
A method of recognizing activity in a video object using an action bank containing a set of template objects, each template object corresponding to an action and having a template sub-vector, the method comprising the steps of:
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