n-grams of action primitives for recognizing human behavior

Authors:
Christian Thurau;Václav Hlaváč
Affiliations:
Czech Technical University, Faculty of Electrical Engineering, Department for Cybernetics, Center for Machine Perception, Czech Republic;Czech Technical University, Faculty of Electrical Engineering, Department for Cybernetics, Center for Machine Perception, Czech Republic
Venue:
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Year:
2007

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Abstract

This paper presents a novel approach for behavior recognition from video data. A biologically inspired action representation is derived by applying a clustering algorithm to sequences of motion images. To obey the temporal context, we express behaviors as sequences of n- grams of basic actions. Novel video sequences are classified by comparing histograms of action n-grams to stored histograms of known behaviors. Experimental validation shows a high accuracy in behavior recognition.