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Proceedings Paper

Robust 3D object model reconstruction from video
Author(s): Po-Hao Huang; Yi-Lin Chen; Chia-Ming Cheng; Yu-An Lu; Shang-Hong Lai
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Paper Abstract

In this paper, we present a 3D object reconstruction system that recovers 3D models of general objects from video. We assume the video of the object is captured from multiple viewpoints. The proposed system is composed of the following components: feature trajectory extraction, 3D structure from motion, surface reconstruction, and texture computation. In the feature trajectory extraction, we compute dense optical flow fields between adjacent frames and aggregate them at the interest points to obtain reliable feature trajectories. In the next structure from motion stage, we develop a robust algorithm to recover the dense 3D structures from several viewpoints for uncalibrated image sequences. For the surface reconstruction from the recovered 3D data points, we develop a new cluster-based radial-basis-function (RBF) algorithm, which overcomes the extensive computational cost limit in a divide-and-conquer manner. For the last texture computation process, we combine multi-view images to form the texture map of the 3D object model. Finally, experimental results are given to show the performance or the proposed 3D reconstruction system.

Paper Details

Date Published: 16 April 2004
PDF: 12 pages
Proc. SPIE 5302, Three-Dimensional Image Capture and Applications VI, (16 April 2004); doi: 10.1117/12.528965
Show Author Affiliations
Po-Hao Huang, National Tsing Hua Univ. (Taiwan)
Yi-Lin Chen, National Tsing Hua Univ. (Taiwan)
Chia-Ming Cheng, National Tsing Hua Univ. (Taiwan)
Yu-An Lu, National Tsing Hua Univ. (Taiwan)
Shang-Hong Lai, National Tsing Hua Univ. (Taiwan)


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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