CASIA OpenIR  > 类脑智能研究中心
Person Identification from Lip Texture Analysis
Zhihe Lu(卢治合)2,3,4; Ran He(赫然)1,2,3,4; He R(赫然)
2017-03
Conference NameInternational Conference on Digital Signal Processing (DSP)
Conference Date2016.10.16-2016.10.18
Conference PlaceBeijing, China
AbstractThe interactive liveness detection for face recognition often requires users to read some digits from 0 to 9. The movement and variation of lip texture during reading potentially
provide discriminative information for human identification. This paper firstly addressed the issue of whether the lip texture during reading can serve as a soft-biometric for person identification. Different from the traditional lip recognition methods that are based on color statistics and lip shapes, we develop a deep architecture that incorporates both CNN and LSTM to jointly model the appearance and the spatial-temporal information of lip texture. We also build a new lip recognition database that contains 11,123 videos for the number 0
9 in Chinese from 57 people. Experimental results show that the proposed method can achieve 96.01% on close-set protocols, suggesting the usage of lip texture as soft-biometrics for facilitating face recognition.
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19721
Collection类脑智能研究中心
Corresponding AuthorHe R(赫然)
Affiliation1.National Laboratory of Pattern Recognition, CASIA
2.Center for Research on Intelligent Perception and Computing, CASIA
3.Center for Excellence in Brain Science and Intelligence Technology, CAS
4.University of Chinese Academy of Sciences, Beijing
Recommended Citation
GB/T 7714
Zhihe Lu,Ran He,He R. Person Identification from Lip Texture Analysis[C],2017.
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