利用时间序列人脸图像提高人脸识别能力

H. Chen, G. Peng, Kai Chi Chang, J. Lin, Yi-Hsin Chen, Yu-Kai Lin, Chao-Yi Huang, Jong-Chen Chen
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引用次数: 3

摘要

近年来,随着计算机视觉相关技术的逐步发展,人脸识别相关技术逐渐成为安防系统的主流方案之一。在本研究中,我们利用 MTCNN[1] 进行预处理,并利用 LRCNs[2] 网络结构和时间序列人脸图像数据,尝试解决由于人脸遮挡或人脸角度等原因造成的用户无法识别的问题,当某一帧无法识别时,我们仍然可以将该用户的特征与其他帧进行比较,从而确定其身份。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enhance Face Recognition Using Time-series Face Images
In recent years, with the gradual development of computer vision-related technologies, the face recognition-related technology has gradually become one of the mainstream security system options. In this study, we use MTCNN[1] for preprocessing and LRCNs[2] network structure and time-series face image data to try to solve the problem of unrecognizable user due to face blocking or face angle, when a frame is unrecognizable, we can still compare the user's characteristics with other frames and determine their identity.
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