Adaptive classifier selection on hierarchical context modeling for robust vision systems

Paper


Jin, SongGuo, Jung, Eun Sung, Bashar, Md. Rezaul, Nam, Mi Young and Rhee, Phill Kyu. 2006. "Adaptive classifier selection on hierarchical context modeling for robust vision systems." Gabrys, Bogdan, Howlett, Robert J. and Jain, Lakhmi C. (ed.) 10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES 2006). Bournemouth, United Kingdom 09 - 11 Oct 2006 Berlin / Heidelberg, Germany. https://doi.org/10.1007/11893011_16
Paper/Presentation Title

Adaptive classifier selection on hierarchical context modeling for robust vision systems

Presentation TypePaper
AuthorsJin, SongGuo (Author), Jung, Eun Sung (Author), Bashar, Md. Rezaul (Author), Nam, Mi Young (Author) and Rhee, Phill Kyu (Author)
EditorsGabrys, Bogdan, Howlett, Robert J. and Jain, Lakhmi C.
Journal or Proceedings TitleLecture Notes in Artificial Intelligence (Book series)
ERA Conference ID43436
Journal Citation4253, pp. 124-134
Number of Pages11
Year2006
Place of PublicationBerlin / Heidelberg, Germany
ISBN9783540465423
Digital Object Identifier (DOI)https://doi.org/10.1007/11893011_16
Web Address (URL) of Paperhttp://springerlink.metapress.com/content/v3226g258764l655/fulltext.pdf
Conference/Event10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)
International Conference on Knowledge-Based and Intelligent Information and Engineering Systems
Event Details
International Conference on Knowledge-Based and Intelligent Information and Engineering Systems
KES
Rank
B
B
B
Event Details
10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)
Parent
International Conference on Knowledge-Based and Intelligent Information and Engineering Systems
Delivery
In person
Event Date
09 to end of 11 Oct 2006
Event Location
Bournemouth, United Kingdom
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

Keywordscontext awareness; face recognition; classifier ensemble; evolvable classifier selection; hierarchical context modeling; genetic algorithm
ANZSRC Field of Research 2020469999. Other information and computing sciences not elsewhere classified
490102. Biological mathematics
460306. Image processing
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Byline AffiliationsInha University, Korea
SeriesLecture Notes in Computer Science
Book TitleKnowledge-based intelligent information and engineering systems
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