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

Alberto Pozo, Miguel A. Patricio, Jesús García and José Manuel Molina

International Journal of Distributed Sensor Networks, 2013, vol. 9, issue 10, 383906

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.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1155/2013/383906 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:9:y:2013:i:10:p:383906

DOI: 10.1155/2013/383906

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().