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Silhouette-based 3-D model reconstruction from multiple images
Date
2003-08-01
Author
Mulayim, AY
Yilmaz, U
Atalay, Mehmet Volkan
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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The goal of this study is to investigate the reconstruction of three-dimensional (3-D) graphical models of real objects in a controlled imaging environment and present the work done in our group based on silhouette-based reconstruction. Although many parts of the whole system have been well-known in the literature and in practice, the main contribution of the paper is that it describes a complete, end-to-end system explained in detail. Based on a multi-image calibration method, an algorithm to extract the rotation axis of a turn-table has been developed. Furthermore, this can be extended to estimate robustly the initial bounding volume of the object to be modeled. The disadvantages of the silhouette-based reconstruction can be removed by an algorithm using photoconsistency. This algorithm his a simpler visibility check, and it eliminates the selection of threshold existing in similar algorithms. Besides, in order to construct the appearance, we use the concept of particles. The reconstruction results are shown both on real world and synthetic objects.
Subject Keywords
Control and Systems Engineering
,
Human-Computer Interaction
,
Electrical and Electronic Engineering
,
Software
,
Information Systems
,
General Medicine
,
Computer Science Applications
URI
https://hdl.handle.net/11511/39573
Journal
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
DOI
https://doi.org/10.1109/tsmcb.2003.814303
Collections
Department of Computer Engineering, Article
Citation Formats
IEEE
ACM
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MLA
BibTeX
A. Mulayim, U. Yilmaz, and M. V. Atalay, “Silhouette-based 3-D model reconstruction from multiple images,”
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
, vol. 33, no. 4, pp. 582–591, 2003, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39573.