3-D Data Acquisition and Shape Recognition by Multiple Views
| Project/Area Number |
60550266
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
計算機工学
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| Research Institution | Faculty of Engineering Science, Osaka University |
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Principal Investigator |
YACHIDA Masahiko Facuty of Engineering Science, Osaka University, 基礎工学部, 助教授 (20029531)
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| Co-Investigator(Kenkyū-buntansha) |
ASADA Minoru Faculty of Engineering Science, Osaka University, 基礎工学部, 助手 (60151031)
TSUJI Saburo Faculty of Engineering Science, Osaka University, 基礎工学部, 教授 (60029527)
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| Project Period (FY) |
1985 – 1986
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| Project Status |
Completed (Fiscal Year 1986)
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| Budget Amount *help |
¥1,600,000 (Direct Cost: ¥1,600,000)
Fiscal Year 1986: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1985: ¥1,000,000 (Direct Cost: ¥1,000,000)
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| Keywords | computer vision / 3-D measurement / object recognition / shape recognition / 形状認識 |
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| Research Abstract |
For recognition of 3-D shape and measurement of 3-D position it is important that a vision system can measure the 3-D data of dense points in the scene. One promising approach is to measure the distance on the basis of the triangulation principle from the disparity of two images. However, a problem of this binocular method is that it is not easy to find correspondence of feature points.
In this research, we propose a new approach for this correspondence problem in which the correspondence problem can be solved geometrically by adding one more camera, that is, by trinocular vision. We have made the trinocular vision system and have made experiments on a variety of objects. From these experiments we have found that the geometrical constraints of the trinocular vision is very powerful for finding correspondence.
However, when the density of edge points increases, chances of points which have multiple candidata points also increase. To solve this problem we also introduced other properties such as similarity of local properties and edge continuity. That is , when there are multiple candidates by geometrical constraints, we check similarity of local properties and edge continuity, and determine the true corresponding point.
Using the above method, we have made experiments and have found that correct correspondence can be established even for complicated scene.
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Report
(1 results)
Research Products
(11 results)
