Face Image Analysis by Unsupervised Learning (The Springer International Series in Engineering and Computer Science, 612, Band 612) - Hardcover

Buch 169 von 260: The Springer International Series in Engineering and Computer Science

Bartlett, Marian Stewart

 
9780792373483: Face Image Analysis by Unsupervised Learning (The Springer International Series in Engineering and Computer Science, 612, Band 612)
Hardcover
ISBN 10: 0792373480 ISBN 13: 9780792373483
Verlag: Springer, 2001

Inhaltsangabe

Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis. It draws upon principles of unsupervised learning and information theory to adapt processing to the immediate task environment. In contrast to more traditional approaches to image analysis in which relevant structure is determined in advance and extracted using hand-engineered techniques, Face Image Analysis by Unsupervised Learning explores methods that have roots in biological vision and/or learn about the image structure directly from the image ensemble. Particular attention is paid to unsupervised learning techniques for encoding the statistical dependencies in the image ensemble.
The first part of this volume reviews unsupervised learning, information theory, independent component analysis, and their relation to biological vision. Next, a face image representation using independent component analysis (ICA) is developed, which is an unsupervised learning technique based on optimal information transfer between neurons. The ICA representation is compared to a number of other face representations including eigenfaces and Gabor wavelets on tasks of identity recognition and expression analysis. Finally, methods for learning features that are robust to changes in viewpoint and lighting are presented. These studies provide evidence that encoding input dependencies through unsupervised learning is an effective strategy for face recognition.
Face Image Analysis by Unsupervised Learning is suitable as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry.

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Verlag
Springer
Erscheinungsdatum
2001
Sprache
Englisch
ISBN 10 
0792373480
ISBN 13 
9780792373483
Einband
Gebundene Ausgabe
Anzahl der Seiten
188
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Vorgestellte Ausgabe

ISBN 10:  1461356539 ISBN 13:  9781461356530
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Softcover