Title :
Regression Nearest Neighbor in Face Recognition
Author :
Yang, Shu ; Zhang, Chao
Author_Institution :
National Lab. on Machine Perception, Peking Univ., Beijing
Abstract :
In this paper, we introduce a regression nearest neighbor framework for general classification tasks. To alleviate potential problems caused by nonlinearity, we propose a kernel regression nearest neighbor (KRNN) algorithm and its convex counterpart (CKRNN) as two specific extensions of nearest neighbor algorithm and present a fast and useful kernel selection method correspondingly. Comprehensive analysis and extensive experiments are used to demonstrate the effectiveness of our methods in real face datasets
Keywords :
face recognition; image classification; regression analysis; convex kernel regression nearest neighbor; face recognition; kernel selection; Algorithm design and analysis; Chaos; Face recognition; Kernel; Laboratories; Lighting; Nearest neighbor searches; Neural networks; Recurrent neural networks; Training data;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.989