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Pose VariantFace Recognition Based on Linear Mapping

Published: 26 February 2018 Publication History

Abstract

Under uncontrolled image conditions, one of the greatest remaining research challenges in face recognition is to recognize faces across different poses. For multi-views face recognition problem either by means of difficult practical three-dimensional methods, either by means of a complex nonlinear transform algorithm. In order to overcome the poses problem, this paper analyzed the spatial change of different pose, regarded the faces with different pose space as a kind of approximate linear relationship by discretion of face pose space. As a consequence, a pose invariant face recognition method based on Orthogonal Procrustes analysis and sparse representation is proposed in this paper. Experimental results demonstrate that the presented algorithm possesses good robustness for the face variation of poses.

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  1. Pose VariantFace Recognition Based on Linear Mapping

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    ICIIT '18: Proceedings of the 2018 International Conference on Intelligent Information Technology
    February 2018
    76 pages
    ISBN:9781450363785
    DOI:10.1145/3193063
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 26 February 2018

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    Author Tags

    1. Face recognition
    2. linear mapping
    3. orthogonal Procrustes analysis
    4. sparse representation

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