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A Feature Selection Approach to the Group Behavior Recognition Issue Using Static Context Information

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URI: http://hdl.handle.net/10016/18274
ISSN: 1550-1329
DOI: 10.1155/2013/383906
UXXI: AR/0000014115
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feature_IJDSN_2013.pdf (2.63 MB)
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2013-06-04
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Hindawi Publishing Corporation
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This paper deals with the problem of group behavior recognition. Our approach is to merge all the possible features of group behavior (individuals, groups, relationships between individuals, relationships between groups, etc.) with static context information relating to particular domains. All this information is represented as a set of features by classification algorithms. This is a very high-dimensional problem, with which classification algorithms are unable cope. For this reason, this paper also presents four feature selection alternatives: two wrappers and two filters. We present and compare the results of each method in the basketball domain.
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Group behavior recognition, static context information
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International Journal of Distributed Sensor Networks (2013), Vol. 2013, pp, 1-11
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