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Cognitive Computation

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01.10.2016

Multi-manifolds Discriminative Canonical Correlation Analysis for Image Set-Based Face Recognition

verfasst von: Haifeng Hu, Jianquan Gu

Erschienen in: Cognitive Computation | Ausgabe 5/2016

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Abstract

In this paper, multi-manifolds discriminative canonical correlation analysis (MMDCCA) is presented for solving face recognition problem with using different image sets. We adopt Linearity-Constrained Hierarchical Agglomerative Clustering algorithm for dividing all image sets into a range of local clusters. Then MMDCCA is proposed to find multiple orthogonal projection functions for maximizing the margins of manifolds with different persons. In order to obtain gains in discrimination accuracy, we enforce a constraint that each person-specific manifold is orthogonal to those of all other manifolds after linear transformation. An efficient sequential iterative learning algorithm is used for finding the discriminative features. Extensive experiments confirm the effectiveness of our model.

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Yasuomi D, Takao N, Keiichi H, Hiroyuki M. The Cognitive Mechanisms of Multi-scale perception for the recognition of extremely similar faces. Cognit Comput. 2015;7(5):501–8.CrossRef

Wang R, Shan S, Chen X, Dai Q, Gao W. Manifold-manifold distance and its application to face recognition with image sets. IEEE Trans Image Process. 2012;21(10):4466–79.CrossRefPubMed

Wang R, Chen X. Manifold discriminant analysis. In: Proceedings of the IEEE conference on computer vision pattern recognition; 2009. pp. 429–36.

Cevikalp H, Triggs B. Face recognition based on image sets. In: Proceedings of the IEEE conference on computer vision pattern recognition; 2010. pp. 2567–73.

Hu Y, Mian A, Owens R. Face recognition using sparse approximated nearest points between image sets. IEEE Trans Pattern Anal Mach Intell. 2012;34(10):1992–2004.CrossRefPubMed

Fan W, Yeung D. Locally linear models on face appearance manifolds with application to dual-subspace based classification. In: Proceedings of the IEEE conference on computer vision pattern recognition; 2006. pp. 1384–90.

Wang T, Shi P. Kernel Grassmannian distances and discriminant analysis for face recognition from image sets. Pattern Recogn Lett. 2009;30(13):1161–5.CrossRef

Jayasumana S, Hartley R, Salzmann M, Li H, Harandi M. Kernel methods on the Riemannian manifold of symmetric positive definite matrices. In: Proceedings of the IEEE conference on computer vision pattern recognition; 2013. pp. 73–80.

Fukui K, Yamaguchi O. Face recognition using multi-viewpoint patterns for robot vision. In: Proceedings of the international symposium of robotics research; 2003. pp. 192–201.

10.

Todros K, Hero AO. On measure transformed canonical correlation analysis. IEEE Trans Image Process. 2012;60(9):4570–85.CrossRef

11.

Chu D, Liao LZ, Ng MK, et al. Sparse canonical correlation analysis: new formulation and algorithm. IEEE Trans Pattern Anal Mach Intell. 2013;35(12):3050–65.CrossRefPubMed

12.

Wolf L, Shashua A. Learning over sets using Kernel principal angles. J Mach Learn Res. 2003;4(10):913–31.

13.

Fukui K, Stenger B, Yamaguchi O. A framework for 3D object recognition using the Kernel constrained mutual subspace method. In: Proceedings of Asian conference computer vision; 2006. pp. 315–24.

14.

Fukui K, Yamaguchi O. The Kernel orthogonal mutual subspace method and its application to 3D object recognition. In: Proceedings of Asian conference computer vision; 2007. pp. 467–76.

15.

Lu J, Tan Y, Wang G, Yang G. Image-to-set face recognition using locality repulsion projections and sparse reconstruction-based similarity measure. IEEE Trans Circuits and Syst Video Technol. 2013;23(6):1070–80.CrossRef

16.

Hu H. Sparse discriminative multi-manifold Grassmannian analysis for face recognition with image sets. IEEE Trans Circuits and Syst Video Technol. 2015;25(10):1599–611.CrossRef

17.

Kim T-K, Arandjelovic O, Cipolla R. Boosted manifold principal angles for image set-based recognition. Pattern Recogn. 2007;40(9):2475–84.CrossRef

18.

Lee K, Yang MH, Kriegman D. Video-based face recognition using probabilistic appearance manifolds. In: Proceedings of the IEEE conference on computer vision pattern recognition; 2003. pp. 313–20.

19.

Gross R, Shi J. The CMU motion of body (MoBo) database. Robotics Institute, Carnegie Mellon Univ., Pittsburgh, PA, Tech. Rep. CMU-RI-TR-01-18; 2001.

20.

Kim M, Kumar S, Pavlovic V, Rowley H. Face tracking and recognition with visual constraints in real-world videos. In: Proceedings of the IEEE conference on computer vision pattern recognition; 2008. pp. 1–8.

21.

Viola P, Jones M. Robust real-time face detection. Int J Comput Vis. 2004;57(2):137–54.CrossRef

22.

Cevikalp H, Triggs B. Face recognition based on image sets. In: Proceedings of the IEEE conference on computer vision pattern recognition; 2010. pp. 2567–73.

Titel: Multi-manifolds Discriminative Canonical Correlation Analysis for Image Set-Based Face Recognition
verfasst von: Haifeng Hu
Jianquan Gu
Publikationsdatum: 01.10.2016
Verlag: Springer US
Erschienen in: Cognitive Computation / Ausgabe 5/2016
Print ISSN: 1866-9956
Elektronische ISSN: 1866-9964
DOI: https://doi.org/10.1007/s12559-016-9403-y

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