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Two-Dimensional Canonical Correlation Analysis of the Logically Concatenated Cross Binary Pattern for Cross Pose Face Recognition

Two-Dimensional Canonical Correlation Analysis of the Logically Concatenated Cross Binary Pattern for Cross Pose Face Recognition

Kumud Arora, Poonam Garg
Copyright: © 2018 |Volume: 8 |Issue: 3 |Pages: 14
ISSN: 2155-6997|EISSN: 2155-6989|EISBN13: 9781522545736|DOI: 10.4018/IJCVIP.2018070104
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MLA

Arora, Kumud, and Poonam Garg. "Two-Dimensional Canonical Correlation Analysis of the Logically Concatenated Cross Binary Pattern for Cross Pose Face Recognition." IJCVIP vol.8, no.3 2018: pp.66-79. http://doi.org/10.4018/IJCVIP.2018070104

APA

Arora, K. & Garg, P. (2018). Two-Dimensional Canonical Correlation Analysis of the Logically Concatenated Cross Binary Pattern for Cross Pose Face Recognition. International Journal of Computer Vision and Image Processing (IJCVIP), 8(3), 66-79. http://doi.org/10.4018/IJCVIP.2018070104

Chicago

Arora, Kumud, and Poonam Garg. "Two-Dimensional Canonical Correlation Analysis of the Logically Concatenated Cross Binary Pattern for Cross Pose Face Recognition," International Journal of Computer Vision and Image Processing (IJCVIP) 8, no.3: 66-79. http://doi.org/10.4018/IJCVIP.2018070104

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Abstract

Face pose recognition is one of the challenging areas in computer vision. Cross-pose change causes the change in the information of face appearance. The maximization of intrasubject correlation helps to widen the intersubject differences which helps further in achieving pose invariance. In this paper, for cross pose recognition, the authors propose to maximize the cross pose correlation by using the logically concatenated cross binary pattern (LC-CBP) descriptor and two dimensional canonical correlation analysis (2DCCA). The LC-CBP descriptor extracts the local texture details of face images with low computation complexity and the 2DCCA explicitly searches for the maximization of the correlated features to retain most informative content. Joint feature consideration via 2DCCA helps in setting up a better correspondence between a discrete set of nonfrontal pose and the frontal pose of the same subject. Experimental results demonstrate the two dimensional canonical correlation LC-CBP descriptor along with intensity values improve the correlation.

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