Titlebook: Subspace Methods for Pattern Recognition in Intelligent Environment; Yen-Wei Chen,Lakhmi C. Jain Book 2014 Springer-Verlag Berlin Heidelbe

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Active Shape Model and Its Application to Face Alignment,e give the model’s position an initial estimate. We adopt a lot of improvements to the classical ASM, such as increasing the width of search profile to reduce the effect of noise, grouping landmarks to avoid mouth shape distort in the search procedure and altering the direction of search profile.

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Independent Component Analysis and Its Application to Classification of High-resolution Remote Sensral independent components are then used for classification of high-resolution remote sensing images. The classification map of the independent components exhibits somewhat spatial consistency, which indicates that reduction of spectral correlation may lead to increase of spatial correlation.

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Tensor-Based Subspace Learning for Multi-pose Face Synthesis,et an identity vector and then the identity vector is used to generate other novel pose images. Our technique is applied onKAO-RitsumeikanMulti-angleView, Illumination and Cosmetic Facial Database(MaVIC) and experimental results show the effectiveness of our proposed method for facial pose synthesis.

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Yen-Wei Chen,Lakhmi C. JainLatest research on the theoretical foundations and applications of subspace methods for pattern recognition using intelligent techniques

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Studies in Computational Intelligencehttp://image.papertrans.cn/t/image/881387.jpg

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Subspace Methods for Pattern Recognition in Intelligent Environment978-3-642-54851-2Series ISSN 1860-949X Series E-ISSN 1860-9503