Abstract
In this paper, we present a novel classification method for eye location. It is based on image context analysis. There is general accord that context can be affluent derivation of information about an illumination, character and diversity of object. However, the problem of how to customize contextual influence is not yet solved clearly. Here we describe a naïve probabilistic method for modeling and testing the images of eye patterns. The proposed eye location method employs context-driven adaptive Bayesian framework to relive the effect due to uneven condition of face image. Based on an easy holistic analysis of face images, the proposed method is able to exactly locate eye position. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously proposed methods.
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© 2007 Springer Berlin Heidelberg
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Koh, E.J., Nam, M.Y., Rhee, P.K. (2007). A Context-Driven Bayesian Classification Method for Eye Location. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71629-7_58
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DOI: https://doi.org/10.1007/978-3-540-71629-7_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71590-0
Online ISBN: 978-3-540-71629-7
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