1991 Fiscal Year Final Research Report Summary
Description of Three-Dimensional Environment by Reliable Stereo Vision
| Project/Area Number |
02452164
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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, Professor, 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)
ASADA Minoru Osaka University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (60151031)
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| Project Period (FY) |
1990 – 1991
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| Keywords | Stereo Vision / Multistage Processing / Zero-Crossing / Feature-based Method / Self-calibration / Sensor Fusion |
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| Research Abstract |
(1) [Reliable stereo] To solve the central problem of finding corresponding points in a pair of stereo images, we extracted features (edges) in the both image and tried to match them according to the similarity of the edge. The image is divided into a small regions (windows) and the matching candidates are obtained in each window. The reliability of matching is evaluated from the histogram of the disparity of the pairs. A multistage method is developed in which matching is tried for reliable edges first, and the less reliable edges are processed later using the previous result.
However, correspondence may not be obtained or may include errors if a window contains discontinuous surfaces. Since a discontinuous surfaces produce T-junctions in an image, the candidates of discontinuous surfaces are detected and matching process is repeated.
Although most conventional stereo visions assume that the position of cameras are known, this does not hold in an actual case. To decrease the error caused by miss alignment, a self calibration method is developed.
(2) [Scene description by reliable stereo] From three-dimensional information obtained by the stereo vision, features are extracted such as discontinuity and abrupt change of surfaces. The geometric description is generated from the features. We developed a method of generating a rich description by combining the range data to gray or color images. The precision of the obtained description depends on the error of three dimensional information. We developed a method of evaluating the reliability of the description, and verified by experiments. A scene is recognized from the description using knowledge about objects.
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