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Proceedings Paper

Hard constrained sparse bundle adjustment of multi-camera with block matrix
Author(s): ZhongChen Shi; JunFeng Sun; Yang Shang; XiaoHu Zhang
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Paper Abstract

Because of the ability to optimize the 3D points and viewing parameters jointly and simultaneously, Sparse Bundle Adjustment (SBA) is an essential procedure and usually used as the last step of Structure from Motion (SFM). Recent development of SBA is incline to research on combination of the numeric method with matrix compression technique for more efficient and less memory consuming, and of prior information with SBA for the high accuracy. In this paper, a new hard constrained SBA method for multi-camera is presented. This method takes the prior information of 3D model or multi-camera into account as a hard constraint, and its solution is accomplished by the Lagrange multiplier method and Schur complement combined and with block matrix. The contribution of this work is that it provides a solution integrate constraint and multi-camera SBA, which is desired in the SFM problem and photogrammetry area. Another noticeable aspect is that obvious less time consuming with block matrix based than without, and the accuracy is maintained.

Paper Details

Date Published: 24 October 2017
PDF: 9 pages
Proc. SPIE 10458, AOPC 2017: 3D Measurement Technology for Intelligent Manufacturing, 104581N (24 October 2017); doi: 10.1117/12.2285619
Show Author Affiliations
ZhongChen Shi, National Univ. of Defense Technology (China)
JunFeng Sun, National Univ. of Defense Technology (China)
China Manned Space Engineering Office (China)
Yang Shang, National Univ. of Defense Technology (China)
XiaoHu Zhang, National Univ. of Defense Technology (China)

Published in SPIE Proceedings Vol. 10458:
AOPC 2017: 3D Measurement Technology for Intelligent Manufacturing
Wolfgang Osten; Anand Krishna Asundi; Huijie Zhao, Editor(s)

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