视频实时人脸识别系统的发展趋势与挑战

V. Vijayakumar
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引用次数: 0

摘要

只提供摘要形式。视频监控系统用于监控监控区域内的活动。现有的视频监控系统是被动的,在事件发生后才进行分析。因此,需要实时的主动解决方案,以避免因异常事件的发生而造成的损害。由于光照、姿态和遮挡的变化,在线视频流中的人脸检测和识别在监控系统中具有挑战性。本主题演讲介绍了有效的人脸识别方法,包括姿态、光照和遮挡的不变性。基于视频的人脸识别系统通过考虑连续帧和时间信息,提高了识别非授权人员的决策能力。基于视频的人脸检测与识别包括人脸检测、姿态估计、特征提取和人脸识别四个模块。实验证明,该模块在精度和检测时间方面是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recent trends and challenges in real time face recognition system in video
Summary form only given. Video surveillance systems are used to monitor the activities in the surveillance area. The existing video surveillance systems are reactive where the analysis is done after the occurrence of an event. Thus, there is a need for a proactive solution in real time to avoid the damage caused due to the occurrence of abnormal events. Face detection and recognition in online video streams plays a challenging role in surveillance system due to variation in illumination, pose and occlusion. This keynote address presents the methodologies for efficient face recognition invariant to Pose, Illumination and Occlusion. Video based face recognition system improves decision making in identifying the unauthorised person by considering continuous frames and temporal information. The video based face detection and recognition involves four modules such as face detection, pose estimation, feature extraction and face recognition. The modules are proved to be efficient in terms of accuracy and detection time.
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