Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/43614
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Type: Journal article
Title: Keyframe Selection for Camera Motion and Structure Estimation from Multiple Views
Author: Thormaehlen, Thorsten
Broszio, Hellward
Weissenfeld, Axel
Citation: Lecture notes in computer science, 2004; 3021:523-535
Part of: Computer Vision – ECCV 2004: 8th European Conference on Computer Vision, Prague, Czech Republic, May 11-14, 2004, Proceedings, Part I / Tomas Pajdla, Jirı Matas (eds.)
Publisher: Springer
Issue Date: 2004
ISBN: 9783540219842
ISSN: 0302-9743
Conference Name: European Conference on Computer Vision (8th : 2004 : Prague, Czech Republic)
ECCV 2004
School/Discipline: School of Computer Science
Statement of
Responsibility: 
Thorsten Thormählen, Hellward Broszio and Axel Weissenfeld
Abstract: Estimation of camera motion and structure of rigid objects in the 3D world from multiple camera images by bundle adjustment is often performed by iterative minimization methods due to their low computational effort. These methods need a robust initialization in order to converge to the global minimum. In this paper a new criterion for keyframe selection is presented. While state of the art criteria just avoid degenerated camera motion configurations, the proposed criterion selects the keyframe pairing with the lowest expected estimation error of initial camera motion and object structure. The presented results show, that the convergence probability of bundle adjustment is significantly improved with the new criterion compared to the state of the art approaches.
Description: The original publication is available at www.springerlink.com
RMID: 0020083007
DOI: 10.1007/b97865
Appears in Collections:Computer Science publications

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