Subspace Methods for Pattern Recognition in Intelligent Environment

✍ Scribed by Yen-Wei Chen, Lakhmi C. Jain (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2014
• Tongue: English
• Leaves: 210
• Series: Studies in Computational Intelligence 552
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages 1-14
Active Shape Model and Its Application to Face Alignment....Pages 1-31
Condition Relaxation in Conditional Statistical Shape Models....Pages 33-56
Independent Component Analysis and Its Application to Classification of High-resolution Remote Sensing Images....Pages 57-81
Subspace Construction from Artificially Generated Images for Traffic Sign Recognition....Pages 83-104
Local Structure Preserving Based Subspace Analysis Methods and Applications....Pages 105-121
Sparse Representation for Image Super-Resolution....Pages 123-150
Sampling and Recovery of Continuously-Defined Sparse Signals and Its Applications....Pages 151-170
Tensor-Based Subspace Learning for Multi-pose Face Synthesis....Pages 171-195
Back Matter....Pages 197-199

✦ Subjects

Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics); Pattern Recognition