Abstract
Although there is much research on face recognition, however, yet now there exist some limitations especially in illumination and pose. This paper addresses a novel framework to prevail over the illumination barrier and a robust vision system. The key ideas of this paper are distributed evolutionary computing and on-line GA that is the combining concept of context-awareness and genetic algorithm. This research implements Fuzzy ART that carries out the context-awareness, modeling, and identification for the context environment and the system can also distinguish changing environments. On-line GA stores the experiences to make context knowledge that is used for on-line adaptation. Finally, supervised learning is applied to carry on recognition experiments. Experimental results on FERET data set show that On-line GA based face recognition performance is significantly benefited over the application of existing GA classification.
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Young, N.M., Bashar, M.R., Rhee, P.K. (2006). A Face Recognition System on Distributed Evolutionary Computing Using On-Line GA. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing in Signal Processing and Pattern Recognition. Lecture Notes in Control and Information Sciences, vol 345. Springer, Berlin, Heidelberg . https://doi.org/10.1007/978-3-540-37258-5_2
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DOI: https://doi.org/10.1007/978-3-540-37258-5_2
Publisher Name: Springer, Berlin, Heidelberg
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