25 September 2003 Application of independent component analysis in face images: a survey
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Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539078
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China
Abstract
Face technologies which can be applied to access control and surveillance, are essential to intelligent vision-based human computer interaction. The research efforts in this field include face detecting, face recognition, face retrieval, etc. However, these tasks are challenging because of variability in view point, lighting, pose and expression of human faces. The ideal face representation should consider the variability so as to we can develop robust algorithms for our applications. Independent Component Analysis (ICA) as an unsupervised learning technique has been used to find such a representation and obtained good performances in some applications. In the first part of this paper, we depict the models of ICA and its extensions: Independent Subspace Analysis (ISA) and Topographic ICA (TICA).Then we summaraize the process in the applications of ICA and its extension in Face images. At last we propose a promising direction for future research.
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Yuchi Huang, Yuchi Huang, Hanqing Lu, Hanqing Lu, } "Application of independent component analysis in face images: a survey", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.539078; https://doi.org/10.1117/12.539078
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