Subspace Methods for Pattern Recognition in Intelligent Environment

• Corporate Author: SpringerLink (Online service)
• Other Authors: Chen, Yen-Wei (Editor), C. Jain, Lakhmi (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
• Series: Studies in Computational Intelligence, 552
• Subjects: Engineering.; Artificial intelligence.; Pattern recognition.; Applied mathematics.; Engineering mathematics.; Appl.Mathematics/Computational Methods of Engineering.; Artificial Intelligence (incl. Robotics).; Pattern Recognition.

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 ext...

Table of Contents:

• Active Shape Model and Its Application to Face Alignment
• Condition Relaxation in Conditional Statistical Shape Models
•  Independent Component Analysis and Its Application to Classification of High-Resolution Remote Sensing Images
• Subspace Construction from Artificially Generated Images for Traffic Sign Recognition
• Local Structure Preserving based Subspace Analysis Methods and Applications
• Sparse Representation for Image Super-Resolution
• Sampling and Recovery of Continuously-Defined Sparse Signals and Its Applications
• Tensor-Based Subspace Learning for Multi-Pose Face Synthesis.