Abstract:An algorithm is proposed, called symmetrical two dimensional principal component analysis (S2DPCA). It is based on the theory of function decomposition in algebra and mirror symmetry in geometry. Firstly, mirror transform is applied to images. Then, the images are decomposed into even and odd symmetrical images, and 2DPCA are performed on the even and odd images respectively. According to the idea of selective ensemble, the more discriminant eigenvectors of the even and odd image space are selected to construct the final eigenspace. Finally, the even and odd 2DPCA features are gotten by projecting samples onto the eigenspace. Both theoretical analysis and experimental results demonstrate that the algorithm can enlarge the number of training samples and raise the recognition rate.
杨万扣,任明武,杨静宇. 基于对称二维主成分分析的人脸识别*[J]. 模式识别与人工智能, 2008, 21(3): 326-331.
YANG WanKou, REN MingWu, YANG JingYu. Face Recognition Based on Symmetrical 2DPCA. , 2008, 21(3): 326-331.
[1] Zhao W, Chellappa R, Rosenfel A, et al. Face Recognition: A Literature Survey. ACM Computing Surveys, 2003, 35(4): 399-458 [2] Zabrodsky H, Peleg S, Avnir D. Symmetry as a Continuous Feature. IEEE Trans on Pattern Analysis and Machine Intelligence, 1995, 17(12):1154-1166 [3] Reisfeld D, Yeshurun Y. Robust Detection of Facial Features by Generalized Symmetry // Proc of the 11th IAPR International Conference on Computer Vision and Applications. The Hague, Netherlands, 1992: 117-120 [4] Kirby M, Sirovich L. Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces. IEEE Trans on Pattern Analysis and Machine Intelligence, 1990, 12(1): 103-108 [5] Etemad K, Chellappa R. Face Recognition Using Discriminant Eigenvector // Proc of the IEEE International Conference of Acoustics, Speech, and Signal Processing. Albuquerque, USA, 1996, Ⅳ: 2148-2151 [6] Yang Qiong, Ding Xiaoqing. Symmetrical PCA and Its Application to Face Recognition. Chinese Journal of Computers, 2003, 26(9): 1146-1151(in Chinese) (杨 琼,丁晓青.对称主分量分析及其在人脸识别中的应用.计算机学报, 2003, 26(9): 1146-1151 ) [7] Bian Zhaoqi, Zhang Xuegong. Pattern Recognition. 2nd Edition. Beijing, China: Tsinghua University Press, 2000 (in Chinese) (边肇祺,张学工.模式识别.第2版.北京:清华大学出版社, 2000) [8] Zheng Yujie, Yang Jingyu, Wu Xiaojun, et al. Feature Extraction Based on Symmetrical ICA and Its Application to Face Recognition. Pattern Recognition and Artificial Intelligence, 2006, 19(1): 116-121 (in Chinese) (郑宇杰,杨静宇,吴小君,等.基于对称ICA的特征抽取方法及其在人脸识别中的应用.模式识别与人工智能, 2006, 19(1): 116-121) [9] Turk M, Pentland A. Eigenfaces for Recognition. Journal of Cognitive Neuroscience, 1991, 3(1): 71-86 [10] Yang Jian, Zhang D, Frangi A F, et al. Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition. IEEE Trans on Pattern Analysis and Machine Intelligence, 2004, 26(1): 131-137 [11] Wang Jue, Zhou Zhihua. Machine Learning and Its Application. Beijing, China: Tsinghua University Press, 2006 (in Chinese) (王 珏,周志华.机器学习及其应用.北京:清华大学出版社, 2006) [12] Krogh A, Vedelsby J. Neural Network Ensembles, Cross Validation, and Active Learning // Tesauro G, Touretzky D S, Leen T K, eds. Advances in Neural Information Processing Systems. Cambridge, USA: MIT Press, 1995, 7: 231-238