Multi-Sensor Face Registration Based on Global and Local Structures

被引:6
作者
Li, Wei [1 ]
Dong, Mingli [2 ]
Lu, Naiguang [2 ]
Lou, Xiaoping [2 ]
Zhou, Wanyong [1 ]
机构
[1] North China Inst Aerosp Engn, Hebei Engn Res Ctr Assembly & Inspect Robot, Langfang 065000, Peoples R China
[2] Beijing Informat Sci & Technol Univ, Minist Educ Optoelect Measurement Technol & Instr, Key Lab, Beijing 100192, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2019年 / 9卷 / 21期
基金
中国国家自然科学基金;
关键词
multi-sensor; face registration; inner-distance; Student's-t Mixtures Model; image fusion; VISIBLE IMAGE FUSION; TRANSFORM; NETWORK;
D O I
10.3390/app9214623
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The work reported in this paper aims at utilizing the global geometrical relationship and local shape feature to register multi-spectral images for fusion-based face recognition. We first propose a multi-spectral face images registration method based on both global and local structures of feature point sets. In order to combine the global geometrical relationship and local shape feature in a new Student's t Mixture probabilistic model framework. On the one hand, we use inner-distance shape context as the local shape descriptors of feature point sets. On the other hand, we formulate the feature point sets registration of the multi-spectral face images as the Student's t Mixture probabilistic model estimation, and local shape descriptors are used to replace the mixing proportions of the prior Student's t Mixture Model. Furthermore, in order to improve the anti-interference performance of face recognition techniques, a guided filtering and gradient preserving image fusion strategy is used to fuse the registered multi-spectral face image. It can make the multi-spectral fusion image hold more apparent details of the visible image and thermal radiation information of the infrared image. Subjective and objective registration experiments are conducted with manual selected landmarks and real multi-spectral face images. The qualitative and quantitative comparisons with the state-of-the-art methods demonstrate the accuracy and robustness of our proposed method in solving the multi-spectral face image registration problem.
引用
收藏
页数:16
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