人脸识别研究取得进展

Lyujun Yue
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引用次数: 1

摘要

人脸识别一直是计算机视觉领域的热门研究任务,其目的是通过分析人脸局部特征(鼻子、嘴巴、眼睛等)之间的关系来识别人,并已广泛应用于公安、移动智能设备、交通等诸多领域。根据是否存在外部遮挡,人脸识别任务主要包括未遮挡人脸识别和更具挑战性的遮挡人脸识别。通过详细的文献调查和分析,本文首先从基于几何特征、基于全局特征、基于局部特征、基于FaceNet和基于弹性图匹配五个方面介绍了具有代表性的非包含人脸识别方法。进一步介绍了遮挡人脸识别的经典方法和原理,并对上述具有代表性的人脸识别算法进行了定量比较和分析。最后,讨论了人脸识别领域存在的问题和未来的发展方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Researches advanced in face recognition
Face recognition has always been a popular research task in the field of computer vision, which aims to identify the people by analyzing the relationship between the local features of the face (nose, mouth, eyes, etc.), and has been widely used in public security, mobile smart devices, transportation and many other fields. Depending on whether there is external occlusion, face recognition task mainly includes unoccluded face recognition and more challenging occluded face recognition. Through a detailed literature survey and analysis, this paper firstly introduces the representative unoccluded face recognition methods from five perspectives: based on geometric features, based on global features, based on local features, based on FaceNet and based on elastic graph matching. The classical methods and principles of occluded face recognition are further introduced, and the above-mentioned representative face recognition algorithms are quantitatively compared and analyzed. Finally, we discuss the remaining problems and future development directions in the field of face recognition.
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