基于SURF和Gabor特征的表情不变人脸识别

Barun Kumar Bairagi, Arpitam Chatterjee, Samir Chandra Das, B. Tudu
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引用次数: 13

摘要

人脸识别是计算机视觉和模式识别领域的一个活跃研究领域。尽管进行了大量的研究和开发,但一种对不同因素(如面部表情、姿势、照明、年龄等)具有强大的时间和记忆效率的方法仍然是一个主要挑战。本文提出了一种基于快速鲁棒特征(SURF)和Gabor滤波的人脸表情不变识别方法。对不同表情的测试图像进行了测试,结果表明该方法比传统的SURF算法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Expressions invariant face recognition using SURF and Gabor features
Face recognition is an active research area in the field of computer vision and pattern recognition. Despite of considerable research and developments a time and memory efficient method that is robust to different factors e.g. facial expressions, pose, illumination, age, etc. remains a major challenges. This paper presents expressions invariant face recognition by detecting the fiducial points and employing speeded up robust feature (SURF) along with Gabor filter. The presented method is tested with test images with different expressions and found to be a better performer over the conventional SURF algorithm.
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