Face recognition using Elastic bunch graph matching

M. Hanmandlu, Divya Gupta, S. Vasikarla
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引用次数: 17

Abstract

A closed-set identification is implemented using Elastic bunch graph matching (EBGM) algorithm. It uses cosine similarity as its matching criterion instead of a classifier for recognition. The proposed method makes use of facial features like fuducial points to differentiate between faces. It is insensitive to variation in facial expressions, illumination and poses on frontal and ¾ frontal images. Experimental results show that the proposed method can achieve a recognition accuracy of 96.67% for the training to test ratio of 7:3 on face images. This method can be extended to provide profile face recognition.
基于弹性束图匹配的人脸识别
利用弹性束图匹配算法实现了闭集识别。它使用余弦相似度作为匹配标准,而不是使用分类器进行识别。该方法利用面部特征,如垂体点来区分人脸。它对正面和3 / 4正面图像上的面部表情、光照和姿势的变化不敏感。实验结果表明,在训练测试比为7:3的情况下,该方法对人脸图像的识别准确率达到96.67%。该方法可以扩展到提供侧面人脸识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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