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A Pose Recovery Algorithm to Minimize the Effects of Pose Variation on the Matching Performance of Elastic Bunch Graph Based Multiview Face Recognition System

机译:一种姿势恢复算法,以最大限度地减少姿势变化对基于弹性束图的匹配性能的影响

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Multiview face recognition is a challenging task of deformable pattern recognition. Machine recognition of human from his/her facial images available at any pose, intensity and expression is the ultimate goal of multiview face recognition system. In the present work the effect of variation of poses on the overall performance of face recognition engine based on elastic bunch graph matching technique is studied using K-means clustering algorithm. A geometry-based pose recovery algorithm is proposed to improve the performance of the system.
机译:多视图人脸识别是可变形模式识别的具有挑战性的任务。从任何姿势,强度和表达的人的面部图像机器识别人类,强度和表达是多视图人脸识别系统的最终目标。在本工作中,使用K-Means聚类算法研究了基于弹性束图匹配技术的面部识别发动机整体性能的变化的影响。提出了一种基于几何的姿势恢复算法来提高系统的性能。

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