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<title>New technique for registration and integration of partial 3D models</title>
Author(s) -
Soon-Yong Park,
Murali Subbarao
Publication year - 2002
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.455242
Subject(s) - epipolar geometry , fundamental matrix (linear differential equation) , computer science , computer vision , transformation matrix , artificial intelligence , rigid transformation , iterative closest point , transformation (genetics) , point set registration , coordinate system , matching (statistics) , point (geometry) , image registration , algorithm , point cloud , mathematics , image (mathematics) , geometry , mathematical analysis , biochemistry , chemistry , physics , kinematics , statistics , classical mechanics , gene
A new technique is introduced for registration and integration of multiple partial 3D models of an object. The technique exploits the epipolar constraint for the multiple- view geometry. Partial 3D shapes of an object from multiple viewing directions are obtained using a digital vision system based on parallel-axis stereo. The vision system is calibrated to obtain an initial transformation matrix for both the stereo imaging geometry and the multiple-view geometry. A multi-resolution stereo matching approach is used for partial 3D shape recovery. The partial 3D shapes are registered approximately using the initial transformation matrix. The initial transformation matrix is then refined by iteratively minimizing the registration error. At this step, a modified Iterative Closest Point (ICP) algorithm is used for matching corresponding points in two different views. A given point in one view is projected to another view using the transformation matrix, and a search is made for a closest point in the other view that lies on the epipolar line. A similar idea is used during partial model integration step to obtain improved results. Partial models are represented as linked lists of segments and integrated segment by segment. Experimental results are presented to show the effectiveness of the new technique.

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