Stereovision depth analysis by two-dimensional motion charge memories |
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| Affiliation: | 1. Departamento de Ingeniería Eléctrica, Electrónica, Automática y Comunicaciones, Escuela Universitaria Politécnica de Cuenca, Universidad de Castilla-La Mancha, 16071 Cuenca, Spain;2. Departamento de Sistemas Informáticos, Escuela Politécnica Superior de Albacete, Universidad de Castilla-La Mancha, 02071 Albacete, Spain;3. Instituto de Investigación en Informática de Albacete (I3A), Universidad de Castilla-La Mancha, 02071 Albacete, Spain;1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;2. Shanghai Shipbuilding Technology Research Institute, Shanghai 200030, China;3. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240, China;4. Shanghai Key Laboratory of Advanced Manufacturing Environment, Shanghai Jiao Tong University, Shanghai 200030, China;1. Department of Applied Electronics, Tokyo University of Science, 6-3-1 Niijuku, Katsushika-ku, Tokyo 125-8585, Japan;2. Department of Material Science, Tokyo University of Science, 6-3-1 Niijuku, Katsushika-ku, Tokyo 125-8585, Japan;1. School of Computer Science and Software Engineering, Shenzhen University, 518060, China;2. Oracle Research and Development Center Shenzhen Co., Ltd., 518057, China;3. Department of Computer Science,Univeristy of Texas at San Antonio, TX 78249, USA;1. Moorfields Eye Hospital, 162 City Road, London EC1V 2PD, United Kingdom;2. Imperial College Healthcare NHS Trust, Western Eye Hospital, Marylebone Road, London NW1 5QH, United Kingdom;3. Focus Clinic, 22 Wimpole Street, London W1G 8GQ, United Kingdom |
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| Abstract: | Several strategies to retrieve depth information from a sequence of images have been described so far. In this paper a method that turns around the existing symbiosis between stereovision and motion is introduced; motion minimizes correspondence ambiguities, and stereovision enhances motion information. The central idea behind our approach is to transpose the spatially defined problem of disparity estimation into the spatial–temporal domain. Motion is analyzed in the original sequences by means of the so-called permanency effect and the disparities are calculated from the resulting two-dimensional motion charge maps. This is an important contribution to the traditional stereovision depth analysis, where disparity is got from the image luminescence. In our approach, disparity is studied from a motion-based persistency charge measure. |
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