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Dynamic vision [electronic resource] : from images to face recognition / Shaogang Gong, Stephen J. McKenna, Alexandra Psarrou.

By: Gong, Shaogang.
Contributor(s): McKenna, Stephen J, 1969- | Psarrou, Alexandra.
Material type: TextTextPublisher: London : Imperial College Press, 2000Description: 1 online resource (xix, 344 p.) : ill.ISBN: 1860943853 (electronic bk.); 9781860943850 (electronic bk.).Subject(s): Human face recognition (Computer science) | Computer vision | Vision par ordinateur | Perception des visages | Apprentissage automatique | Intelligence artificielle | R�eseaux neuronaux (Informatique) | COMPUTERS -- Computer Vision & Pattern RecognitionGenre/Form: Electronic books.Additional physical formats: Print version:: Dynamic vision.DDC classification: 006.3/7 Online resources: EBSCOhost
Contents:
pt. I. Background. 1. About Face. 2. Perception and Representation. 3. Learning under Uncertainty -- pt. II. From Sensory to Meaningful Perception. 4. Selective Attention: Where to Look. 5. A Face Model: What to Look For. 6. Understanding Pose. 7. Prediction and Adaptation -- pt. III. Models of Identity. 8. Single-View Identification. 9. Multi-View Identification. 10. Identifying Moving Faces -- pt. IV. Perception in Context. 11. Perceptual Integration. 12. Beyond Faces -- App. A. Databases -- App. B. Commercial Systems -- App. C. Mathematical Details.
Summary: Face recognition is a task that the human vision system seems to perform almost effortlessly, yet the goal of building computer-based systems with comparable capabilities has proven to be difficult. The task implicitly requires the ability to locate and track faces through often complex and dynamic scenes. Recognition is difficult because of variations in factors such as lighting conditions, viewpoint, body movement and facial expression. Although evidence from psychophysical and neurobiological experiments provides intriguing insights into how we might code and recognise faces, its bearings o.
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Includes bibliographical references (p. 315-338) and index.

pt. I. Background. 1. About Face. 2. Perception and Representation. 3. Learning under Uncertainty -- pt. II. From Sensory to Meaningful Perception. 4. Selective Attention: Where to Look. 5. A Face Model: What to Look For. 6. Understanding Pose. 7. Prediction and Adaptation -- pt. III. Models of Identity. 8. Single-View Identification. 9. Multi-View Identification. 10. Identifying Moving Faces -- pt. IV. Perception in Context. 11. Perceptual Integration. 12. Beyond Faces -- App. A. Databases -- App. B. Commercial Systems -- App. C. Mathematical Details.

Description based on print version record.

Face recognition is a task that the human vision system seems to perform almost effortlessly, yet the goal of building computer-based systems with comparable capabilities has proven to be difficult. The task implicitly requires the ability to locate and track faces through often complex and dynamic scenes. Recognition is difficult because of variations in factors such as lighting conditions, viewpoint, body movement and facial expression. Although evidence from psychophysical and neurobiological experiments provides intriguing insights into how we might code and recognise faces, its bearings o.

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