Face Analysis in the Wild

F. H. B. Zavan, Nathaly Gasparin, Julio Cesar Batista, Luan P. e Silva, Vítor Albiero, O. Bellon, Luciano Silva
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引用次数: 4

Abstract

With the global demand for extra security systems, and the growing of human-machine interaction, facial analysis in unconstrained environments (in the wild) became a hot-topic in recent computer vision research.Unconstrained environments include surveillance footage, social media photos and live broadcasts.This type of images and videos include no control over illumination, position, size, occlusion, and facial expressions. Successful facial processing methods for controlled scenarios are unable to pledge with challenging circumstances. Consequently, methods tailored for handling those situations are indispensable for the face analysis research progress. This work presents a comprehensive review of state-of-the-art methods, drawing attention to the complications derived from in the wild scenarios and the behavior differences when applied to the controlled images.The main topics to be covered are: (1) face detection; (2) facial image quality; (3) head pose estimation; (4) face alignment; (5) 3D face reconstruction; (6) gender and age estimation; (7) facial expressions and emotions; and (8) face recognition. Finally, available code and applications for in the wild face analysis are presented,followed by a discussion on future directions.
野外人脸分析
随着全球对额外安全系统的需求以及人机交互的增长,无约束环境下的面部分析成为近年来计算机视觉研究的热点。不受约束的环境包括监控录像、社交媒体照片和直播。此类图像和视频无法控制照明、位置、大小、遮挡和面部表情。成功的面部处理方法在受控情况下无法保证具有挑战性的情况。因此,为处理这些情况而量身定制的方法是人脸分析研究进展必不可少的。这项工作提出了一个全面的审查,最先进的方法,提请注意的复杂性,从野生情景和行为差异,当应用于控制图像。主要涉及的主题有:(1)人脸检测;(2)面部图像质量;(3)头姿估计;(4)面对齐;(5)三维人脸重建;(6)性别、年龄估算;(七)面部表情和情绪;(8)人脸识别。最后,给出了野外人脸分析的可用代码和应用,并对未来的发展方向进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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