| Project/Area Number |
04452194
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| Research Category |
Grant-in-Aid for General Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
情報工学
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| Research Institution | Osaka University |
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Principal Investigator |
SHIRAI Yoshiaki Osaka University, Faculty of Engineering, Processor, 工学部, 教授 (50206273)
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| Co-Investigator(Kenkyū-buntansha) |
MIURA Jun Osaka University, Faculty of Engineering, Research Associate, 工学部, 助手 (90219585)
KUNO Yoshinori Osaka University, Faculty of Engineering, Associate Processor, 工学部, 助教授 (10252595)
浅田 稔 大阪大学, 工学部, 助教授 (60151031)
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| Project Period (FY) |
1992 – 1993
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| Project Status |
Completed (Fiscal Year 1993)
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| Budget Amount *help |
¥5,900,000 (Direct Cost: ¥5,900,000)
Fiscal Year 1993: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1992: ¥5,000,000 (Direct Cost: ¥5,000,000)
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| Keywords | Motion image processing / Filtering / DSP / Optical flow / Moving object / Tracking / Region segmentation / Uncertainty / オプティカルフロー |
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| Research Abstract |
An algorithm for optical flow vector detection is studied which obtains the flow vector at each pixel by applying multiple filters and solving the equations derived from the filtered images. A special purpose device is developed for performing the algorithm at a high speed. The device consists of serially connected boards with two DSPs, and extracts flow vectors in the image 15 times a second by pipeline processing. The DSP program is made and the optimal filters were determined by experiments. A method is developed for extracting reliable flow vectors with multiple filters and obtaining regions with the uniform motion. If boundaries of objects are ambiguous from two images, accurate regions and the motions are determined by using more than two images. Moving object tracking processing is applied to real images. When an object region is specified, the centroid of the object is obtained from the optical flow, and the object is tracked by controlling the pan and tilt of a camera so that the object may be in the center of the image. The algorithm is implemented in the special purpose device, and a moving object is tracked in real time. In order to deal with motion changes during a long sequence of images, spatio-temporal segmentation is studied based on the Minimum Description Length (MDL) principle. In the method, longer edges are first extracted, and they are segmented spatially and temporally. Then using models of the movement, the final spatio-temporal segmentation is performed based on the MDL principle.
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