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학술대회 Graph-Based Robust Shape Matching for Robotic Application
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주한별, 정예근, Olivier Duchenne, 고성영, 권인소
International Conference on Robotics and Automation (ICRA) 2009, pp.1207-1213
09MS3500, 방통융합형 Full 3D 복원 기술 개발(표준화연계), 구본기
Shape is one of the useful information for object detection. The human visual system can often recognize objects based on the 2-D outline shape alone. In this paper, we address the challenging problem of shape matching in the presence of complex background clutter and occlusion. To this end, we propose a graph-based approach for shape matching. Unlike prior methods which measure the shape similarity without considering the relation among edge pixels, our approach uses the connectivity of edge pixels by generating a graph. A group of connected edge pixels, which is represented by an "edge"of the graph, is considered together and their similarity cost is defined for the "edge"weight by explicit comparison with the corresponding template part. This approach provides the key advantage of reducing ambiguity even in the presence of background clutter and occlusion. The optimization is performed by means of a graph-based dynamic algorithm. The robustness of our method is demonstrated for several examples including long video sequences. Finally, we applied our algorithm to our grasping robot system by providing the object information in the form of prompt hand-drawn templates.
KSP 제안 키워드
Background clutter, Complex background, Dynamic algorithm, Graph-based Approach, Hand-drawn, Human Visual System(HVS), Object detection, Robot System, Shape similarity, edge pixels, recognize objects