title: Multiview discriminative geometry preserving projection for image classification.
abstract: In many image classification applications, it is common to extract multiple visual features from different views to describe an image. Since different visual features have their own specific statistical properties and discriminative powers for image classification, the conventional solution for multiple view data is to concatenate these feature vectors as a new feature vector. However, this simple concatenation strategy not only ignores the complementary nature of different views, but also ends up with "curse of dimensionality." To address this problem, we propose a novel multiview subspace learning algorithm in this paper, named multiview discriminative geometry preserving projection (MDGPP) for feature extraction and classification. MDGPP can not only preserve the intraclass geometry and interclass discrimination information under a single view, but also explore the complementary property of different views to obtain a low-dimensional optimal consensus embedding by using an alternating-optimization-based iterative algorithm. Experimental results on face recognition and facial expression recognition demonstrate the effectiveness of the proposed algorithm.
authors.affiliation: School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China.
authors.forename: Ziqiang
authors.identifier: 0000-0001-5633-1608
authors.initials: Z
authors.lastname: Wang
authors.affiliation: School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China.
authors.forename: Xia
authors.initials: X
authors.lastname: Sun
authors.affiliation: School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China.
authors.forename: Lijun
authors.initials: L
authors.lastname: Sun
authors.affiliation: School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China.
authors.forename: Yuchun
authors.initials: Y
authors.lastname: Huang
mesh_terms: D000465:Algorithms; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated
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