Discriminant orthogonal rank-one tensor projections for face recognition

Authors:
Chang Liu;Kun He;Ji-liu Zhou;Chao-Bang Gao
Affiliations:
College of Information Science and Technology, Chengdu University, and Key Laboratory of Pattern Recognition and Intelligent Information Processing of Sichuan, and School of Computer Science, Sich ...;School of Computer Science, Sichuan University, Chengdu, China;School of Computer Science, Sichuan University, Chengdu, China;College of Information Science and Technology, Chengdu University, and Key Laboratory of Pattern Recognition and Intelligent Information Processing of Sichuan, and School of Computer Science, Sich ...
Venue:
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Year:
2011

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Abstract

Traditional face recognition algorithms are mostly based on vector space. These algorithms result in the curse of dimensionality and the small-size sample problem easily. In order to overcome these problems, a new discriminant orthogonal rank-one tensor projections algorithm is proposed. The algorithm with tensor representation projects tensor data into vector features in the orthogonal space using rank-one projections and improves the class separability with the discriminant constraint. Moreover, the algorithm employs the alternative iteration scheme instead of the heuristic algorithm and guarantees the orthogonality of rank-one projections. The experiments indicate that the algorithm proposed in the paper has better performance for face recognition.