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Face recognition in complex backgrounds

机译:复杂背景下的人脸识别

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摘要

Face recognition has higher performance with controlled illumination and pose. But in some applications such as video surveillance, imaging condition is uncontrolled and the subject is not cooperative. In this paper pose invariant face recognition in complex backgrounds is discussed and a framework is proposed. Our algorithm is comprised of four parts. In the first part a face location algorithm combining face feature and template is proposed to determine the face location, represented as center of eyes and mouth. In the second part a face segmentation algorithm using curve fitting is proposed to segment face region in the image. The third part is face normalization------to obtain a front view face from a face with variant pose. In the forth part, the face recognition based on normalized faces is implemented using eigenface method. The algorithm is tested using 70 images of 14 persons, the experimental results confirm the efficiency of our algorithms.
机译:面部识别在照明和姿势受控的情况下具有更高的性能。但是在某些应用中,例如视频监视,成像条件不受控制,对象无法配合。本文讨论了复杂背景下的姿势不变人脸识别,并提出了一个框架。我们的算法包括四个部分。在第一部分中,提出了一种结合人脸特征和模板的人脸定位算法来确定人脸位置,以眼睛和嘴巴的中心表示。在第二部分中,提出了一种使用曲线拟合的人脸分割算法来分割图像中的人脸区域。第三部分是人脸归一化-从具有不同姿势的人脸获得前视人脸。第四部分,使用特征脸方法实现了基于标准化脸部的脸部识别。该算法使用了14个人的70张图像进行了测试,实验结果证实了我们算法的有效性。

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