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View-based active appearance models

Affiliation:	1. Division of Imaging Science and Biomedical Engineering, Stopford Building, University of Manchester, Oxford Road, M13 9PT Manchester, UK;2. Image-Metrics PLC, Regent House, Heaton Lane, Stockport SK4 3LE, UK;1. Dipartimento di Fisica “E. R. Caianiello”, Università di Salerno and CNISM, Unità di Salerno, I-84084 Fisciano (Salerno), Italy;2. Dipartimento di Fisica, Università di Napoli Federico II, I-80125 Napoli, Italy;1. Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China;2. Beijing University of Posts and Telecommunications Hospital, Beijing, China;3. Beijing Stomatological Hospital & School of Stomatology, Capital Medical University, Beijing, China;1. Department of Electronics, Deendayal Upadhyay College, University of Delhi, Delhi, India;2. Department of Computer Science, University of Delhi, Delhi, India;3. Department of Computer Science, Deendayal Upadhyay College, University of Delhi, Delhi, India

Abstract:	We demonstrate that a small number of 2D linear statistical models are sufficient to capture the shape and appearance of a face from a wide range of viewpoints. Such models can be used to estimate head orientation and track faces through large angles. Given multiple images of the same face we can learn a coupled model describing the relationship between the frontal appearance and the profile of a face. This relationship can be used to predict new views of a face seen from one view and to constrain search algorithms which seek to locate a face in multiple views simultaneously.

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