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【答案】应助回帖
★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★
感谢参与，应助指数 +1
佰斯特: 金币+10, ★★★★★最佳答案 2014-08-25 09:42:29
jssxh: 金币+5, 检索EPI+1, 谢谢参与，请继续关注本版块！ 2014-08-25 20:31:53
Accession number:
20143017984728
Title: Facial expression recognition under partial occlusion based on gabor multi-orientation features fusion and local gabor binary pattern histogram sequence
Authors: Liu, Shuai-Shi1 Email author liu-shuaishi@126.com; Zhang, Yan1 Email author 260259423@qq.com; Liu, Ke-Ping1 Email author liukeping@mail.ccut.edu.cn; Li, Yan1
Author affiliation: 1 School of Electrical and Electronic Engineering, Changchun University of Technology, Changchun, China
Corresponding author: Liu, S.-S. (liu-shuaishi@126.com)
Source title: Proceedings - 2013 9th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2013
Abbreviated source title: Proc. - Int. Conf. Intelligent Inf. Hiding Multimedia Signal Process., IIH-MSP
Monograph title: Proceedings - 2013 9th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2013
Issue date: 2013
Publication year: 2013
Pages: 218-222
Article number: 6846619
Language: English
ISBN-13: 9780769551203
Document type: Conference article (CA)
Conference name: 9th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2013
Conference date: October 16, 2013 - October 18, 2013
Conference location: Beijing, China
Conference code: 106451
Sponsor: Beijing University of Technology; Beijing Wuzi University; et al.; IEEE Beijing Section; IEEE Tainan Section; National Kaohsiung University of Applied Sciences
Publisher: IEEE Computer Society
Abstract: In this paper, we propose a novel facial expression recognition method under partial occlusion based on Gabor multi-orientation features fusion and local Gabor binary pattern histogram sequence (LGBPHS). Firstly, the Gabor filter is adopted to extract multi-scale and multi-orientation features. Secondly, the Gabor magnitudes of different orientations in the same scale will be fused according to the fusion rule in this paper and then the fusion features are further encoded by using the LBP operator. Finally, the fused image is divided into several non-overlapping rectangle units with equal size, and the histogram of each unit is computed and combined as facial expression features. The proposed method is robust to partial occlusion and better recognition rates are achieved in JAFFE database with eyes occlusion and mouth occlusion. Experimental results show that the method is effective to facial expression recognition under partial occlusion. © 2013 IEEE.
Number of references: 13
Main heading: Face recognition
Controlled terms: Gesture recognition - Graphic methods - Multimedia signal processing
Uncontrolled terms: Expression recognition - Facial expression recognition - Facial Expressions - Features fusions - Fusion features - LGBPHS - Local Gabor binary patterns - Partial occlusions
Classification code: 716 Telecommunication; Radar, Radio and Television - 716.1 Information Theory and Signal Processing - 902.1 Engineering Graphics
DOI: 10.1109/IIH-MSP.2013.63
Database: Compendex
Compilation and indexing terms, © 2014 Elsevier Inc. |
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