Applied Pattern Recognition
Published on 11. April 2008
Book
Hardback
XII, 246 pages
978-3-540-76830-2 (ISBN)
Description
A sharp increase in the computing power of modern computers, accompanied by a decrease in the data storage costs, has triggered the development of extremely powerful algorithms that can analyze complex patterns in large amounts of data within a very short period of time. Consequently, it has become possible to apply pattern recognition techniques to new tasks characterized by tight real-time requirements (e.g., person identification) and/or high complexity of raw data (e.g., clustering trajectories of mobile objects). The main goal of this book is to cover some of the latest application domains of pattern recognition while presenting novel techniques that have been developed or customized in those domains.
More details
Series
Edition
2008 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
59 s/w Abbildungen, 51 farbige Abbildungen
XII, 246 p. 110 illus., 51 illus. in color.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 21 mm
Weight
606 gr
ISBN-13
978-3-540-76830-2 (9783540768302)
DOI
10.1007/978-3-540-76831-9
Schweitzer Classification
Other editions
Additional editions
Horst Bunke | Abraham Kandel | Mark Last
Applied Pattern Recognition
Book
11/2010
Springer
€160.49
Shipment within 7-9 days
Content
Face Recognition Applications.- Skin-based Face Detection-Extraction and Recognition of Facial Expressions.- Facial Image Processing.- Face Recognition and Pose Estimation with Parametric Linear Subspaces.- Spatio-Temporal Patterns.- 4D Segmentation of Cardiac Data Using Active Surfaces with Spatiotemporal Shape Priors.- Measuring Similarity Between Trajectories of Mobile Objects.- Graph-Based Methods.- Matching of Hypergraphs - Algorithms, Applications, and Experiments.- Feature-Driven Emergence of Model Graphs for Object Recognition and Categorization.- Special Applications.- A Wavelet-based Statistical Method for Chinese Writer Identification.- Texture Analysis by Accurate Identification of a Generic Markov-Gibbs Model.