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Proceedings Paper

Integration method for 3D model reconstruction
Author(s): Xiaokun Li; William G. Wee
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Paper Abstract

Three-dimensional (3D) object reconstruction from range images plays an important role in many research and application fields, including computer vision, reverse engineering, computer graphics, and CAD/CAM. Since data integration is a fundamental step in object reconstruction, a great number of research efforts have been made on that. In this paper, a novel integration algorithm is presented. Firstly, the input data (registered data) which contains overlapping data is represented by kd-tree structure. Then, three theorems are provided together with the usage of nearest neighbor searching to identify and eliminate the overlapping data. The method manipulates the registered data directly without preprocessing work, therefore, provides an efficient and straightforward way to remove the redundant data. This is different from the traditional methods which need to mesh the input data or build an implicit surface function before integration. To reduce the data size and obtain a reasonable density distribution, a reliable resampling method called ball travel based resampling is also developed. The experimental results demonstrate the efficiency of the proposed algorithm.

Paper Details

Date Published: 16 April 2004
PDF: 11 pages
Proc. SPIE 5302, Three-Dimensional Image Capture and Applications VI, (16 April 2004); doi: 10.1117/12.525989
Show Author Affiliations
Xiaokun Li, Univ. of Cincinnati (United States)
William G. Wee, Univ. of Cincinnati (United States)

Published in SPIE Proceedings Vol. 5302:
Three-Dimensional Image Capture and Applications VI
Brian D. Corner; Peng Li; Roy P. Pargas, Editor(s)

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