Deep learning based forensic face verification in videos

被引:0
作者
Zeng, Jinhua [1 ]
Zeng, Jinfeng [1 ]
Qiu, Xiulian [1 ]
机构
[1] Minist Justice, Inst Forens Sci, Shanghai 200063, Peoples R China
来源
PROCEEDINGS OF 2017 IEEE INTERNATIONAL CONFERENCE ON PROGRESS IN INFORMATICS AND COMPUTING (PIC 2017) | 2017年
关键词
deep learning; forensic identification of human images; face identification; face verification; winner-take-all; EIGENFACES;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Deep learning for face identification-verification application has been proven to be fruitful. Human faces constituted the main information for human identification besides gait, body silhouette, etc. Deep learning for forensic face identification could provide quantitative indexes for face similarity measurement between the questioned and the known human faces in cases, which had the advantage of result objectivity without expert experience influences. We studied the deep learning based face representation for forensic verification of human images. Its application strategies and technical limitations were discussed. We proposed a "winner-take-all" strategy in the case of the forensic identification of human images in videos. We expected the theories and techniques for forensic identification of human images in which both qualitative and quantitative analysis methods were included and expert judgment and automatic identification methods were coexisted.
引用
收藏
页码:77 / 80
页数:4
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