Local Descriptors for Spatio-temporal Recognition

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Local Descriptors for Spatio-temporal Recognition
Abstract. This paper presents and investigates a set of local spacetime descriptors for representing and recognizing motion patterns in video. Following the idea of local features in the spatial domain, we use the notion of space-time interest points and represent video data in terms of local space-time events. To describe such events, we define several types of image descriptors over local spatio-temporal neighborhoods and evaluate these descriptors in the context of recognizing human activities. In particular, we compare motion representations in terms of spatio-temporal jets, position dependent histograms, position independent histograms, and principal component analysis computed for either spatio-temporal gradients or optic flow. An experimental evaluation on a video database with human actions shows that high classification performance can be achieved, and that there is a clear advantage of using local position dependent histograms, consistent with previously reported findings...
Ivan Laptev, Tony Lindeberg
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Authors Ivan Laptev, Tony Lindeberg
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