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| Facial Expression Recognition under Partial Occlusion Based on Gabor Multi-orientation Features Fusion and Local Gabor Binary Pattern Histogram Sequence |
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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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