FaSTIP: a new method for detection and description of space-time interest points for human activity classification

Authors:
Soumitra Samanta;Bhabatosh Chanda
Affiliations:
Indian Statistical Institute, Kolkata;Indian Statistical Institute, Kolkata
Venue:
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Year:
2012

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Abstract

This paper presents a new method to detect space time interest point (STIP) from video data. We use three dimensional facet model to detect STIP and call it as facet space-time interest point or FaSTIP. The proposed algorithm detects all the desired interest points efficiently in different scales compared to other existing methods. A video clip is described as a collection of 3D wavelet base features computed at these interest points. Finally, multi-channel SVM with χ2- kernel is used to classify human actions. Our contribution here are two fold: first, we present a new algorithm for interest point detection in video data, and second, we propose a new descriptor for general human activity classification. Experimental results show the accuracy of the detected interest points and the power of descriptor compared to the state-of-the-art.