光照鲁棒人脸识别的自动频带选择

H. K. Ekenel, R. Stiefelhagen
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引用次数: 9

摘要

不同的光照条件会引起面部外观的剧烈变化,从而导致人脸识别算法的性能显著下降。为了克服这一问题,本文采用了一种自动频段选择方案。该方法结合了一种基于局部外观的人脸识别算法,该算法采用离散余弦变换(DCT)对局部人脸区域进行处理。该方法从提取的DCT系数中确定应用于分类的DCT系数。在扩展的耶鲁人脸数据库B上进行的大量实验表明,受益于频率信息可以在不断变化的光照条件下提供鲁棒的人脸识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Frequency Band Selection for Illumination Robust Face Recognition
Varying illumination conditions cause a dramatic change in facial appearance that leads to a significant drop in face recognition algorithms' performance. In this paper, to overcome this problem, we utilize an automatic frequency band selection scheme. The proposed approach is incorporated to a local appearance-based face recognition algorithm, which employs discrete cosine transform (DCT) for processing local facial regions. From the extracted DCT coefficients, the approach determines to the ones that should be used for classification. Extensive experiments conducted on the extended Yale face database B have shown that benefiting from frequency information provides robust face recognition under changing illumination conditions.
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