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Image-Set Based Collaborative Representation for Face Recognition in Videos

机译:视频中基于图像集的人脸识别协同表示

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Video-based face recognition has become one of the hottest topics in the domain of face recognition because it has a wide range of applications in multi-media processing conference, human-computer interaction, judicature identification, video surveillance, and entrance controlling, etc. Methods of video based face recognition could be divided to be two main aspects: the models used to represent the individual image sets; and the similarity metric used to compare the models. Based on image-set based object classification methods, we present an image-set based on collaborative representation based classification (SCRC) method for face recognition in videos. Firstly, the query face video is divided to be many sub sets. Secondly, every sub set is represented by the collaborative representation based classification. Finally, we combine the recognition results of sub sets to be a final classification. Experiments test on three public video face datasets, the experimental results demonstrate that the proposed SCRC method can be able to outperform a number of existing state-of-the-art ones.
机译:基于视频的人脸识别已成为人脸识别领域最热门的话题之一,因为它在多媒体处理会议,人机交互,司法识别,视频监控和入口控制等方面具有广泛的应用。基于视频的面部识别方法可以分为两个主要方面:用于表示单个图像集的模型;以及用于比较模型的相似性指标。基于基于图像集的对象分类方法,我们提出了一种基于基于协作表示的分类(SCRC)方法的图像集,用于视频中的人脸识别。首先,将查询面部视频划分为许多子集。其次,每个子集都由基于协作表示的分类表示。最后,我们将子集的识别结果组合为最终分类。对三个公共视频面部数据集进行了实验测试,实验结果表明,所提出的SCRC方法可以胜过许多现有的最新技术。

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