A cloud-based monitoring system via face recognition using Gabor and CS-LBP features |
| |
Authors: | Chen Li Wei Wei Jiaxue Li Wei Song |
| |
Affiliation: | 1.School of Computer Science and Technology,North China University of Technology,Beijing,People’s Republic of China;2.Beijing Key Laboratory on Integration and Analysis of Large-scale Stream Data,North China University of Technology,Beijing,People’s Republic of China;3.School of Electronic and Information Engineering,North China University of Technology,Beijing,People’s Republic of China |
| |
Abstract: | Face detection and recognition is an important topic in security. Currently, ubiquitous monitoring has received a large amount of attention. This paper proposes a cloud-based ubiquitous monitoring system via face recognition. It consists of a monitoring client module for face detection and recognition and a cloud storage module for data visualization. In the monitoring client module, the center-symmetric local Gabor binary pattern feature extraction method is proposed for face recognition, which combines improved multi-scale Gabor and center-symmetric local binary pattern (CS-LBP) features. This method maintains crucial local features, reduces the Gabor filter complexity, and adds rotational invariance and more precise texture information. A large number of experiments on the ORL, Yale-B, and Yale databases show that the proposed method obtains significantly better recognition rates than the LBP, CS-LBP, and Scale Gabor methods. Furthermore, we propose a Web browser-based data visualization that renders the geographic locations of the face detection and recognition results. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|