To purchase hard copies of this book, please email:
orders@intechopen.com
By only printing on demand InTech ensures our carbon footprint is kept to a minimum.
The data below shows the environmental impact of printing one single book:
36.36 kg wood
1.96 g CO2
33.02 ml Water
Share this page
New Approaches to Characterization and Recognition of Faces
Edited by Peter Corcoran, ISBN 978-953-307-515-0, Hard cover, 252 pages, Publisher: InTech, Published: August 01, 2011 under CC BY-NC-SA 3.0 license, in subject Artificial Intelligence
DOI: 10.5772/994
As a baby, one of our earliest stimuli is that of human faces. We rapidly learn to identify, characterize and eventually distinguish those who are near and dear to us. We accept face recognition later as an everyday ability. We realize the complexity of the underlying problem only when we attempt to duplicate this skill in a computer vision system. This book is arranged around a number of clustered themes covering different aspects of face recognition. The first section presents an architecture for face recognition based on Hidden Markov Models; it is followed by an article on coding methods. The next section is devoted to 3D methods of face recognition and is followed by a section covering various aspects and techniques in video. Next short section is devoted to the characterization and detection of features in faces. Finally, you can find an article on the human perception of faces and how different neurological or psychological disorders can affect this.
This book is indexed in:
Book contents
- Chapter 1Automatic Face Recognition System for Hidden Markov Model Techniques
- Chapter 2Large-Scale Face Image Retrieval: A Wyner-Ziv Coding Approach
- Chapter 33D Face Recognition
- Chapter 4Face Image Synthesis and Interpretation Using 3D Illumination-Based AAM Models
- Chapter 5Processing and Recognising Faces in 3D Images
- Chapter 6Real-Time Video Face Recognition for Embedded Devices
- Chapter 7Video Based Face Recognition Using Convolutional Neural Network
- Chapter 8Adaptive Fitness Approach - an Application for Video-Based Face Recognition
- Chapter 9Real Time Robust Embedded Face Detection Using High Level Description
- Chapter 10Face Discrimination Using the Orientation and Size Recognition Characteristics of the Spreading Associative Neural Network
- Chapter 11The Methodology for Facial Features Detection
- Chapter 12Exploring and Understanding the High Dimensional and Sparse Image Face Space: a Self-Organized Manifold Mapping
- Chapter 13The Effects of Right/Left Temporal Lobe Lesions on the Recognition of Familiar Faces
