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On-line Stereo Self-calibration through Minimization of Matching Costs

Tobias Langner, Raúl Rojas— 2013

This paper presents an approach to the problem of on-line stereo self-calibration. After a short introduction of the general method, we propose a new one, based on the minimization of matching costs. We furthermore show that the number of matched pixels can be used as a quality measure. A Metropolis algorithm based Monte-Carlo scheme is employed to reliably minimize the costs. We present expermental results in the context of automotive stereo with different matching algorithms. These show the effectiveness for the calibration of roll and pitch angle offsets.

TitelOn-line Stereo Self-Calibration
VerfasserTobias Langner, Raúl Rojas
VerlagSpringer-Verlag
Themaself-calibration, stereo vision, matching costs
Datum20130617
KennungPrint ISBN 978-3-642-38885-9; Online ISBN 978-3-642-38886-6, DOI 10.1007/978-3-642-38886-6_51
Quelle/n
Erschienen inProceedings of the 18th Scandinavian Conference on Image Analysis, Espoo, Finland. Lecture Notes in Computer Science, Vol. 7944.
Größe oder Längepp. 545-554