Subspace Methods for Pattern Recognition in Intelligent Environment

丛 书 名：Studies in Computational Intelligence

版本说明：1

作     者：Yen-Wei Chen, Lakhmi C. Jain (eds.) 

I S B N：(纸本) 9783642548505;9783642548512 

出 版 社：Springer-Verlag Berlin Heidelberg 

出 版 年：2014年

页      数：210页

主 题 词：Pattern recognition systems Computer vision 

学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 13[艺术学] 081104[工学-模式识别与智能系统] 08[工学] 0804[工学-仪器科学与技术] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 

摘      要：This research book provides a comprehensive overview of the state-of-the-art subspace learning methods for pattern recognition in intelligent environment. With the fast development of internet and computer technologies, the amount of available data is rapidly increasing in our daily life. How to extract core information or useful features is an important issue. Subspace methods are widely used for dimension reduction and feature extraction in pattern recognition. They transform a high-dimensional data to a lower-dimensional space (subspace), where most information is retained. The book covers a broad spectrum of subspace methods including linear, nonlinear and multilinear subspace learning methods and applications. The applications include face alignment, face recognition, medical image analysis, remote sensing image classification, traffic sign recognition, image clustering, super resolution, edge detection, multi-view facial image synthesis.