Orthogonal filter banks with region Log-TiedRank covariance matrices for face recognition

Citation

Ng, Cong Jie and Low, Cheng Yaw and Toh, Kar Ann and Kim, Jaihie and Teoh, Andrew Beng Jin (2018) Orthogonal filter banks with region Log-TiedRank covariance matrices for face recognition. Journal of Visual Communication and Image Representation, 55. pp. 548-560. ISSN 1047-3203

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Abstract

With the capability of fusing varying features from a specific image region, the Region Covariance Matrices (RCM) image descriptor has been evidenced plausible in face recognition. However, a systematic study for RCM, regarding which features to be fused in particular, remains absent. This paper therefore explores several features derived from the orthogonal filter ensembles, i.e., Identity Transform, Discrete Haar Transform, Discrete Cosine Transform, and Karhunen-Loève Transform, for feature encoding in RCM. Aside from that, we also outline a RCM variant, dubbed Region Log-TiedRank Covariance Matrices (RLTCM) in this paper. The RLTCM descriptor, on average, exhibits dramatic performance gain over RCM as well as state-of-the-art descriptors, especially when probe sets far deviated from the face gallery. Furthermore, we discern that the RLTCM descriptor defined based on Identity Transform, i.e., the simplest form of orthogonal filters, and other learning-free orthogonal filters yield impressive performance on par with the learning-based counterparts.

Item Type: Article
Uncontrolled Keywords: Biometric identification, Orthogonal filters, Region covariance matrices, Log-TiedRank, Face recognition
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 14 Mar 2021 19:26
Last Modified: 14 Mar 2021 19:26
URII: http://shdl.mmu.edu.my/id/eprint/7456

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