Group Sparse Multiview Patch Alignment Framework With View Consistency for Image Classification

No single feature can satisfactorily characterize the semantic concepts of an image. Multiview learning aims to unify different kinds of features to produce a consensual and efficient representation. This paper redefines part optimization in the patch alignment framework (PAF) and develops a group s...

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Veröffentlicht in:	IEEE transactions on image processing 2014-07, Vol.23 (7), p.3126-3137
Hauptverfasser:	Gui, Jie, Tao, Dacheng, Sun, Zhenan, Luo, Yong, You, Xinge, Tang, Yuan Yan
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Alignment Applied sciences Consistency Correlation Detection, estimation, filtering, equalization, prediction Electronic mail Equations Exact sciences and technology Feature extraction Image classification Image color analysis Image processing Information, signal and communications theory Kernel Learning Optimization Signal and communications theory Signal processing Signal representation. Spectral analysis Signal, noise Telecommunications and information theory Transformations
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