Human Face Recognition Using Third-Order Synthetic Neural Networks

✍ Scribed by Okechukwu A. Uwechue, Abhijit S. Pandya (auth.)

• Publisher: Springer US
• Year: 1997
• Tongue: English
• Leaves: 131
• Series: The Springer International Series in Engineering and Computer Science 410
• Edition: 1
• Category: Library

✦ Synopsis

Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-order networks require little training data (hence, short training times) and have been used to perform transformation-invariant recognition of relatively simple visual patterns, achieving very high recognition rates. The successful results of these methods provided inspiration to address more practical problems which have grayscale as opposed to binary patterns (e.g., alphanumeric characters, aircraft silhouettes) and are also more complex in nature as opposed to purely edge-extracted images - human face recognition is such a problem.
Human Face Recognition Using Third-Order Synthetic Neural Networks serves as an excellent reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.

✦ Table of Contents

Front Matter....Pages i-xv
Introduction....Pages 1-20
Face Recognition....Pages 21-35
Implementation of Invariances....Pages 37-45
Simple Pattern Recognition....Pages 47-55
Facial Pattern Recognition....Pages 57-90
Network Training....Pages 91-109
Conclusions & Contributions....Pages 111-114
Future Work....Pages 115-117
Back Matter....Pages 119-123

✦ Subjects

Multimedia Information Systems;Statistical Physics, Dynamical Systems and Complexity;Computer Imaging, Vision, Pattern Recognition and Graphics;Image Processing and Computer Vision