Adaptive classifier selection on hierarchical context modeling for robust vision systems

Jin, SongGuo and Jung, Eun Sung and Bashar, Md. Rezaul and Nam, Mi Young and Rhee, Phill Kyu (2006) Adaptive classifier selection on hierarchical context modeling for robust vision systems. In: 10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES 2006), 9-11 Oct 2006, Bournemouth, UK.

Abstract

This paper proposes a hierarchical image context based adaptable classifier ensemble for efficient visual information processing under uneven illumination environments. In the proposed method, classifier ensemble is constructed in two stages: i) it distinguishes the illumination context of input image in terms of hierarchical context modeling and ii) constructs classifier ensemble using the genetic algorithm (GA). It stores its experiences in terms of the illumination context hieratical manner and derives artificial chromosome so that the context knowledge can be accumulated and used for identification purpose. The proposed method operates in two modes: the learning mode and the action mode. It can improve its performance incrementally using GA in the learning mode. Once sufficient context knowledge is accumulated, the method can operate in real-time. The proposed method has been evaluated in the area of face recognition. The superiority of the proposed method has been shown using international face database FERET


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Author version not held.
Depositing User: Ms Leslie Blay
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 24 May 2010 06:28
Last Modified: 02 Jul 2013 23:55
Uncontrolled Keywords: context awareness; face recognition; classifier ensemble; evolvable classifier selection; hierarchical context modeling; genetic algorithm
Fields of Research (FOR2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
01 Mathematical Sciences > 0102 Applied Mathematics > 010202 Biological Mathematics
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: doi: 10.1007/11893011_16
URI: http://eprints.usq.edu.au/id/eprint/8145

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