利用特征变换的跨姿态人脸识别

2006 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety Pub Date : 2006-10-01 DOI:10.1109/CIHSPS.2006.313297

Hongzhou Zhang, Yongping Li, Lin Wang, Chengbo Wang

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引用次数: 0

摘要

人脸识别是一种先进的识别解决方案，可以满足安防领域的需求。姿态效应对该技术的稳健应用是一个巨大的挑战。我们提出了一种特征变换方法来处理头部在半轮廓视图内的大致旋转。与基于计算机视觉技术的算法相比，所提出的特征变换方法不依赖于大量的计算量，易于在实际环境中应用。在FERET数据库上探讨了常用的特征提取方法、最小二乘(LS)和总最小二乘(TLS)的计算方法以及变换的一些性质

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Face Recognition across Poses Utilizing Feature Transformation

Face recognition is an advanced identification solution which can meet the crying needs in security areas. Pose effect is a big challenge for robust applications of this technology. We proposed a feature transformation approach to cope with the head rotation roughly within half profile view. Comparing with algorithms based on computer vision technology, the proposed feature transformation method is not dependent on heavy computation and easily to apply in live conditions. Popular feature extractions, least square (LS) and total least square (TLS) solution in calculating as well as some properties of transformation were explored on the FERET database

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2006 IEEE International Conference on Computational Intelligence for Homeland Security and Personal Safety

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