A survey on heterogeneous face recognition: Sketch, infra-red, 3D and low-resolution

被引：73
作者：
Ouyang, Shuxin [1 ,2 ]
Hospedales, Timothy [2 ]
Song, Yi-Zhe [2 ]
Li, Xueming [1 ]
Loy, Chen Change [3 ]
Wang, Xiaogang [3 ]
机构：
[1] Beijing Univ Posts & Telecommun, 10 Xituchen St, Beijing, Peoples R China
[2] Queen Mary Univ London, London E1 4NS, England
[3] Chinese Univ Hong Kong, Shatin, Hong Kong, Peoples R China
来源：
IMAGE AND VISION COMPUTING | 2016年 / 56卷
关键词：
Cross-modality face recognition; Heterogeneous face recognition; Sketch-based face recognition; Visual-infrared matching; 2D-3D matching; High-low resolution matching; DISCRIMINANT-ANALYSIS; FEATURES; SUPERRESOLUTION;
D O I：
10.1016/j.imavis.2016.09.001
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Heterogeneous face recognition (HFR) refers to matching face imagery across different domains. It has received much interest from the research community as a result of its profound implications in law enforcement. A wide variety of new invariant features, cross-modality matching models and heterogeneous datasets are being established in recent years. This survey provides a comprehensive review of established techniques and recent developments in HFR. Moreover, we offer a detailed account of datasets and benchmarks commonly used for evaluation. We finish by assessing the state of the field and discussing promising directions for future research. (C) 2016 Elsevier B.V. All rights reserved.
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收藏
页码：28 / 48
页数：21
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