The use of genetic algorithm for feature selection in video concept detection

Momtazpour, M; Saraee, MH; Palhang, M

Abstract

Video semantic concept detection is considered as an important research problem by the multimedia industry in recent years. Classification is the most accepted method used for concept detection, where, the output of the classification system is interpreted as semantic concepts. These concepts can be employed for automatic indexing, searching and retrieval of video objects. However, employed features have high dimensions and thus, concept detection with the existing classifiers experiences high computation complexity. In this paper, a new approach is proposed to reduce the classification complexity and the required time for learning and classification by choosing the most important features. For this purpose genetic algorithms are employed as a feature selector. Simulation results illustrate improvements in the behavior of the classifier.

Citation

Momtazpour, M., Saraee, M., & Palhang, M. (2010, May). The use of genetic algorithm for feature selection in video concept detection. Presented at The 18th Iranian Conference on Electrical Engineering (ICEE), 2010, Isfahan Iran

• Presentation Conference Type: Other
• Conference Name: The 18th Iranian Conference on Electrical Engineering (ICEE), 2010
• Conference Location: Isfahan Iran
• Start Date: May 11, 2010
• End Date: May 13, 2010
• Publication Date: Jul 8, 2010
• Deposit Date: Nov 3, 2011
• Book Title: 2010 18th Iranian Conference on Electrical Engineering
• DOI: https://doi.org/10.1109/IRANIANCEE.2010.5507016
• Publisher URL: http://dx.doi.org/10.1109/IRANIANCEE.2010.5507016
• Additional Information: Event Type : Conference