Accurate Mouth State Estimation via Convolutional Neural Networks | |
Cao, Jie1,2; Li, Haiqing1,2; Sun, Zhenan1,2; He, Ran1,2 | |
2017 | |
会议名称 | International Conference on Digital Signal Processing |
会议日期 | 2016年10月16日 - 2016年10月18日 |
会议地点 | 北京 |
摘要 | Human mouth is very flexible such that its status (closed or open) is often used as a judgment in the liveness detection of face recognition. However, due to large head pose and illumination variations, accurate mouth status estimation is still challenging in real-world scenarios. In this paper, we propose a deep convolutional neural networks (CNNs) method for mouth status estimation under unconstrained conditions and different types of attacks. Different from previous methods that extract hand-crafted features and then treat the estimation problem as a binary classification task, our method automatically extracts discriminative features via learned convolutional and the pooling layers. To demonstrate the effectiveness of our method and the challenge of mouth status estimation in real-world, we also propose a mouth status estimation dataset that contains 10,714 images in the wild. Experimental results with two types of liveness attacks show that our proposed method outperforms the other traditional methods, especially in the wild condition. |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/19843 |
专题 | 智能感知与计算研究中心 |
作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学 |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Cao, Jie,Li, Haiqing,Sun, Zhenan,et al. Accurate Mouth State Estimation via Convolutional Neural Networks[C],2017. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
07868531.pdf(1231KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 | ||
Accurate Mouth State(1231KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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