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Proceedings Paper

Genetic algorithm for bundle adjustment in aerial panoramic stitching
Author(s): Chunxiao Zhang; Gaojin Wen; Chunnan Wu; Hongmin Wang; Zhiming Shang; Qian Zhang
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Paper Abstract

This paper presents a genetic algorithm for bundle adjustment in aerial panoramic stitching. Compared with the conventional LM (Levenberg-Marquardt) algorithm for bundle adjustment, the proposed bundle adjustment combining the genetic algorithm optimization eliminates the possibility of sticking into the local minimum, and not requires the initial estimation of desired parameters, naturally avoiding the associated steps, that includes the normalization of matches, the computation of homography transformation, the calculations of rotation transformation and the focal length. Since the proposed bundle adjustment is composed of the directional vectors of matches, taking the advantages of genetic algorithm (GA), the Jacobian matrix and the normalization of residual error are not involved in the searching process. The experiment verifies that the proposed bundle adjustment based on the genetic algorithm can yield the global solution even in the unstable aerial imaging condition.

Paper Details

Date Published: 4 March 2015
PDF: 5 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94431G (4 March 2015); doi: 10.1117/12.2178852
Show Author Affiliations
Chunxiao Zhang, Beijing Institute of Space Mechanics and Electricity (China)
Gaojin Wen, Beijing Institute of Space Mechanics and Electricity (China)
Chunnan Wu, Beijing Institute of Space Mechanics and Electricity (China)
Hongmin Wang, Beijing Institute of Space Mechanics and Electricity (China)
Zhiming Shang, Beijing Institute of Space Mechanics and Electricity (China)
Qian Zhang, Beijing Institute of Space Mechanics and Electricity (China)


Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

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