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

publication date

  • junio 2013

start page

  • 1

end page

  • 11

volume

  • 2013

international standard serial number (ISSN)

  • 1550-1329

electronic international standard serial number (EISSN)

  • 1550-1477

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.