Human action recognition using distribution of oriented rectangular patches
Date
2007-10Source Title
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animatio, 2007
Publisher
Springer
Pages
271 - 284
Language
English
Type
Conference PaperItem Usage Stats
271
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298
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Abstract
We describe a "bag-of-rectangles" method for representing and recognizing human actions in videos. In this method, each human pose in an action sequence is represented by oriented rectangular patches extracted over the whole body. Then, spatial oriented histograms are formed to represent the distribution of these rectangular patches. In order to carry the information from the spatial domain described by the bag-of-rectangles descriptor to temporal domain for recognition of the actions, four different methods are proposed. These are namely, (i) frame by frame voting, which recognizes the actions by matching the descriptors of each frame, (ii) global histogramming, which extends the idea of Motion Energy Image proposed by Bobick and Davis by rectangular patches, (iii) a classifier based approach using SVMs, and (iv) adaptation of Dynamic Time Warping on the temporal representation of the descriptor. The detailed experiments are carried out on the action dataset of Blank et. al. High success rates (100%) prove that with a very simple and compact representation, we can achieve robust recognition of human actions, compared to complex representations. © Springer-Verlag Berlin Heidelberg 2007.
Keywords
Data reductionData structures
Image analysis
Image reconstruction
Support vector machines
Rectangular patches
Spatial domains
Spatial oriented histograms
Gesture recognition