A Feature Selection Approach to the Group Behavior Recognition Issue Using Static Context Information. (8th October 2013)

• Record Type: Journal Article
• Authors: Pozo, Alberto; Patricio, Miguel A.; García, Jesús; Molina, José Manuel
• Other Names: Corchado Juan Manuel Academic Editor.
• Is Part Of: International journal of distributed sensor networks. (2013)
• Publication Date: 2013-10-08
• Subjects: Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1155/2013/383906
• Languages: English
• ISSNs: 1550-1329

Abstract

Abstract : 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.