.png){kind=icon}
返回
Reference Face Graph for Face Recognition
.png){kind=icon}
OA
AI
DOI：10.1109/TIFS.2014.2359548.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Face recognition has been studied extensively; however, real-world face recognition still remains a challenging task. The demand for unconstrained practical face recognition is rising with the explosion of online multimedia such as social networks, and video surveillance footage where face analysis is of significant importance. In this paper, we approach face recognition in the context of graph theory. We recognize an unknown face using an external reference face graph (RFC). An REG is generated and recognition of a given face is achieved by comparing it to the faces in the constructed RFC. Centrality measures are utilized to identify distinctive faces in the reference face graph. The proposed RFC-based face recognition algorithm is robust to the changes in pose and it is also alignment free. The REG recognition is used in conjunction with DCT locality sensitive hashing for efficient retrieval to ensure scalability. Experiments are conducted on several publicly available databases and the results show that the proposed approach outperforms the state-of-the-art methods without any preprocessing necessities such as face alignment. Due to the richness in the reference set construction, the proposed method can also handle illumination and expression variation.
Keyword:
Face recognition
graph analysis
centrality measure
alignment-free
pose robust
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
8
论文数:
5.2K
被引数:
2.3W
机构
引用论文
Face identification using reference-based features with message passing model.png)
NEUROCOMPUTINGOAAI
NEUROCOMPUTINGIF6.5
OAAI分享收藏分享收藏
查看更多内容