3D Face Detection via Reconstruction over Hierarchical Features for Single Face Situations
文献类型：期刊论文
| 作者 | Yu, Bo1; Lane, Ian1; Chen, Fang1 |
| 刊名 | International Journal of Pattern Recognition and Artificial Intelligence
 |
| 出版日期 | 2016 |
| 卷号 | 30期号:4 |
| 关键词 | 3-DIMENSIONAL SLOPE STABILITY SPECTRAL-ELEMENT METHOD WENCHUAN EARTHQUAKE HYBRID METHOD TAIWAN SURFACES REGION MOTION CHINA AREA |
| 通讯作者 | Chen, Fang (chenfang@radi.ac.cn) |
| 英文摘要 | There are multiple challenges in face detection, including illumination conditions and diverse poses of the user. Prior works tend to detect faces by segmentation at pixel level, which are generally not computationally efficient. When people are sitting in the car, which can be regarded as single face situations, most face detectors fail to detect faces under various poses and illumination conditions. In this paper, we propose a simple but efficient approach for single face detection. We train a deep learning model that reconstructs face directly from input image by removing background and synthesizing 3D data for only the face region. We apply the proposed model to two public 3D face datasets, and obtain significant improvements in false rejection rate (FRR) of 4.6% (from 4.6% to 0.0%) and 21.7% (from 30.2% to 8.5%), respectively, compared with state-of-art performances in two datasets. Furthermore, we show that our reconstruction approach can be applied using 1/2 the time of a widely used real-time face detector. These results demonstrate that the proposed Reconstruction ConNet (RN) is both more accurate and efficient for real-time face detection than prior works. © 2016 World Scientific Publishing Company. |
| 学科主题 | Computer Science |
| 类目[WOS] | Computer Science, Artificial Intelligence |
| 收录类别 | SCI ; EI |
| 语种 | 英语 |
| WOS记录号 | WOS:20161202141383 |
| 源URL | [http://ir.radi.ac.cn/handle/183411/39382]  |
| 专题 | 遥感与数字地球研究所_SCI/EI期刊论文_期刊论文 |
| 作者单位 | 1. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China 2. Carnegie Mellon University, NASA, Research Park 23, Moffett Field 3.CA, United States 4. Hainan Key Laboratory of Earth Observation, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Sanya, China |
| 推荐引用方式 GB/T 7714 | Yu, Bo,Lane, Ian,Chen, Fang. 3D Face Detection via Reconstruction over Hierarchical Features for Single Face Situations[J]. International Journal of Pattern Recognition and Artificial Intelligence,2016,30(4). |
| APA | Yu, Bo,Lane, Ian,&Chen, Fang.(2016).3D Face Detection via Reconstruction over Hierarchical Features for Single Face Situations.International Journal of Pattern Recognition and Artificial Intelligence,30(4). |
| MLA | Yu, Bo,et al."3D Face Detection via Reconstruction over Hierarchical Features for Single Face Situations".International Journal of Pattern Recognition and Artificial Intelligence 30.4(2016). |
入库方式： OAI收割
来源：遥感与数字地球研究所
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