[1]TONG Ying.Local binary pattern based on the directions and its application in facial expression recognition[J].CAAI Transactions on Intelligent Systems,2015,10(3):422-428.[doi:10.3969/j.issn.1673-4785.201405016]
Copy
Local binary pattern based on the directions and its application in facial expression recognition
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
10
Number of periods:
2015 3
Page number:
422-428
Column:
学术论文—机器感知与模式识别
Public date:
2015-06-25
- Title:
- Local binary pattern based on the directions and its application in facial expression recognition
- Keywords:
- facial expression recognition; local binary pattern (LBP); central nearest neighbor classification; directional local binary pattern (DLBP); Gabor; local directional pattern (LDP)
- CLC:
- TP391.41
- DOI:
- 10.3969/j.issn.1673-4785.201405016
- Abstract:
- The traditional local binary pattern (LBP) algorithm for facial expression recognition could not describe the gray value change in different directions of somel expression regions, such as eyes, mouth, forehead, etc. The recognition result is not satisfied. This paper presents a simple and robust method, namely local binary pattern based on the directions (DLBP), which improves the coding pattern of LBP and encoded the difference from the horizontal, vertical and diagonal directions. Experimental results on JAFFE and Cohn-Kanade databases show that DLBP algorithm has achieved 5% and 1% higher recognition rates than other existing algorithms, such as LBP and Gabor. It has a strong robustness to Gaussian noise and salt and pepper noise compared with LBP, and Its feature extraction time is reduced by 50% compared to LDP. Therefore, the DLBP algorithm is a fast and effective feature descriptor.
- References:
-
[1] HUANG Di, SHAN Caifeng, ARDABILIAN M, et al. Local binary patterns and its application to facial image analysis: a survey[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 2011, 41(6): 765-781.
[2] KYPEROUNTAS M, TEFAS A, PITAS I. Salient feature and reliable classifier selection for facial expression classification[J]. Pattern Recognition, 2010, 43(3): 972-986.
[3] OU Jun, BAI Xiaobo, PEI Yun, et al. Automatic facial expression recognition using Gabor filter and expression analysis[C]//Second International Conference on Computer Modeling and Simulation (ICCMS). Sanya, China, 2010: 215-218.
[4] LI P, PHUNG S L, BOUZERDOUM A, et al. Improved facial expression recognition with trainable 2-D filters and support vector machines[C]//20th International Conference on Pattern Recognition (ICPR). Istanbul, Turkey, 2010: 3732-3735.
[5] 张文超, 山世光, 张洪明, 等. 基于局部Gabor变化直方图序列的人脸描述与识别[J]. 软件学报, 2006, 17(12): 2508-2517. ZHANG Wenchao, SHAN Shiguang, ZHANG Hongming, et al. Histogram sequence of local Gabor binary pattern for face description and identification[J]. Journal of Software, 2006, 17(12): 2508-2517.
[6] 徐洁, 章毓晋. 基于多种采样方式和Gabor特征的表情识别[J]. 计算机工程, 2011, 37(18): 195-197. XU Jie, ZHANG Yujin. Expression recognition based on variant sampling method and Gabor features[J]. Computer Engineering, 2011, 37(18): 195-197.
[7] AHMED F. Gradient directional pattern: a robust feature descriptor for facial expression recognition[J]. Electronics Letters, 2012, 48(19): 1203-1204.
[8] HUANG Xiaohua, ZHAO Guoying, ZHENG Wenming, et al. Spatiotemporal local monogenic binary patterns for facial expression recognition[J]. IEEE Signal Processing Letters, 2012, 19(5): 243-246.
[9] JABID T, KABIR M H, CHAE O. Robust facial expression recognition based on local directional pattern[J]. ETRI Journal, 2010, 32(5): 784-794.
[10] ZHANG Baochang, GAO Yongsheng, ZHAO Sanqing, et al. Local derivative pattern versus local binary pattern: face recognition with high-order local pattern descriptor[J]. IEEE Transactions on Image Processing, 2010, 19(2): 533-544.
[11] 王玮, 黄非非, 李见为, 等. 使用多尺度LBP特征描述与识别人脸[J]. 光学精密工程, 2008, 16(4): 696-705. WANG Wei, HUANG Feifei, LI Jianwei, et al. Face description and recognition using multi-scale LBP feature[J]. Optics and Precision Engineering, 2008, 16(4): 696-705.
[12] 王玮, 黄非非, 李见为, 等. 采用LBP金字塔的人脸描述与识别[J]. 计算机辅助设计与图形学学报, 2009, 21(1): 94-100, 106.WANG Wei, HUANG Feifei, LI Jianwei, et al. Face description and recognition by LBP pyramid[J]. Journal of Computer Aided Design & Computer Graphics, 2009, 21(1): 94-100, 106.
[13] TAN Xiaoyang, TRIGGS B. Enhanced local texture feature sets for face recognition under difficult lighting conditions[J]. IEEE Transactions on Image Processing, 2010, 19(6): 1635-1650.
[14] YANG Hong, WANG Yiding. A LBP-based face recognition method with Hamming distance constraint[C]//Fourth International Conference on Image and Graphics. Beijing, China, 2007: 645-649.
[15] HUANG Di, WANG Yunhong, WANG Yiding. A robust method for near infrared face recognition based on extended local binary pattern[M]//BEBIS G, BOYLE R, PARVIN B, et al. Advances in Visual Computing. Berlin/Heidelberg: Springer, 2007: 437-446.
[16] 阮锦新. 多姿态人脸检测与表情识别关键技术研究[D]. 广州: 华南理工大学, 2010: 64-83. RUAN Jinxin. Study on key technology for multi-pose face detection and facial expression recognition[D]. Guangzhou, China: South China University of Technology, 2010: 64-83.
[17] PRIYA G N, BANU R S D W. Person independent facial expression detection using MBWM and multiclass SVM[J]. International Journal of Computer Applications, 2012, 55(17): 52-58.
[18] 付晓峰. 基于二元模式的人脸识别与表情识别研究[D]. 杭州: 浙江大学, 2008: 54-65. FU Xiaofeng. Research on binary pattern-based face recognition and expression recognition[D]. Hangzhou, China: Zhejiang University, 2008: 54-65.
[19] LAJEVARDI S M, HUSSAIN Z M. Higher order orthogonal moments for invariant facial expression recognition[J]. Digital Signal Processing, 2010, 20(6): 1771-1779.
[20] RAHULAMATHAVAN Y, PHAN R C W, CHAMBERS J A, et al. Facial expression recognition in the encrypted domain based on local fisher discriminant analysis[J]. IEEE Transactions on Affective Computing, 2013, 4(1): 83-92.
- Similar References:
Memo
-
Last Update:
2015-07-15