Face recognitionLaplacianfacesLocality Preserving Projection (LPP)Face recognition has recently become a hot research topic. In order to do more in that area, several algorithms have emerged. However, even the most efficient algorithm has limitations. To overcome this problem, the combination of ...
Face Recognition Using Laplacianfaces. We propose an appearance-based face recognition method called the Laplacianface approach. By using Locality Preserving Projections (LPP), the face images a... X He,S Yan,Y Hu,... - 《IEEE Transactions on Pattern Analysis & Machine Intelligence》 被引量: ...
Face recognition using Laplacianfaces IEEE Trans. Pattern Anal. Mach. Intell. (2005) K. Fukunaga Introduction to Statistical Pattern Recognition (1990) B.V.K.V. Kumar et al. Correlation pattern recognition for face recognition Proc. IEEE. (2006) C. Xie et al. Redundant class-dependence featur...
Face recognition using Laplacianfaces IEEE Trans. Pattern Anal. Mach. Intell. (2005) H. Hotelling Analysis of a complex of statistical variables into principal components J. Edu. Psychol. (1933) R.A. Fisher The use of multiple measurements in taxonomic problems Ann. Eug. (1936) X.F. He,...
He, X., Yan, S., Hu, Y., Niyogi, P., Zhang, H.: Face Recognition Using Laplacianfaces. IEEE Trans. Pattern Analysis and Machine Intelligence 27(3), 328–340 (2005) CrossRef Ahonen, T., Hadid, A., Pietikäinen, M.: Face Recognition with Local Binary Patterns. In: Pajdla, ...
In this paper we propose a two-dimensional (2D) Laplacianfaces method for face recognition. The new algorithm is developed based on two techniques, i.e., locality preserved embedding and image based projection. The 2D Laplacianfaces method is not only computationally more efficient but also more ...
Face recognition using nonparametric-weighted Fisherfaces[J] . Dong-Lin Li,Mukesh Prasad,Sheng-Chih Hsu,Chao-Ting Hong,Chin-Teng Lin.EURASIP Journal on Advances in Signal Processing . 2012 (1)Dong-Lin Li, Mukesh Prasad, Sheng-Chih Hsu, Chao-Ting Hong and Chin-Teng Lin: Face recognition ...
这里翻译下《Deep face recognition: a survey v4》. 1 引言 由于它的非侵入性和自然特征,人脸识别已经成为身份识别中重要的生物认证技术,也已经应用到许多领域,如军事,进入,公共安全和日常生活。FR自然在CVPR会议中也占据了十分长的时间。早在1990年代,随着特征脸的提出[157],FR就成为了一个比较热门的研究领域。
Face recognition using laplacianfaces IEEE Trans. Pattern Anal. Mach. Intell. (2005) S. Yan, D. Xu, B. Zhang, H.-J. Zhang, “Graph embedding: A general framework for dimensionality reduction,” Computer...View more references Cited by (441) HCFNN: High-order coverage function neural net...
Xiamen University ℑ Institute of Artificial Intelligence, Xiamen University Abstract In recent years, Face Image Quality Assessment (FIQA) has become an indispensable part of the face recognition system to guarantee the stability and reliability of recogn...