.png){kind=icon}
返回
Robust Face Recognition from Multi-View Videos
.png){kind=icon}
OA
AI
DOI：10.1109/TIP.2014.2300812.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Multiview face recognition has become an active research area in the last few years. In this paper, we present an approach for video-based face recognition in camera networks. Our goal is to handle pose variations by exploiting the redundancy in the multiview video data. However, unlike traditional approaches that explicitly estimate the pose of the face, we propose a novel feature for robust face recognition in the presence of diffuse lighting and pose variations. The proposed feature is developed using the spherical harmonic representation of the face texture-mapped onto a sphere; the texture map itself is generated by back-projecting the multiview video data. Video plays an important role in this scenario. First, it provides an automatic and efficient way for feature extraction. Second, the data redundancy renders the recognition algorithm more robust. We measure the similarity between feature sets from different videos using the reproducing kernel Hilbert space. We demonstrate that the proposed approach outperforms traditional algorithms on a multiview video database.
Keyword:
Face recognition
pose variations
multi-camera networks
spherical harmonics
期刊
IF:
13.7
论文数:
1.0W
被引数:
8.4W
机构
引用论文
A Nuclear Localization Sequence Endows Human Pancreatic Ribonuclease with Cytotoxic Activity.png)
Biochemistry
BiochemistryIF0
PREAI
分享收藏Robust Tracking in A Camera Network: A Multi-Objective Optimization Framework摄像机网络中的鲁棒跟踪: 一个多目标优化框架
PREAI
分享收藏
查看更多内容