ROCHADE: Robust Checkerboard Advanced Detection for Camera Calibration

Placht S, Fürsattel P, Assoumou Mengue E, Hofmann H, Schaller C, Balda M, Angelopoulou E (2014)


Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2014

Publisher: Springer

Edited Volumes: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

City/Town: Heidelberg

Book Volume: 8692

Pages Range: 766-779

Edition: 1

Conference Proceedings Title: Lecture Notes in Computer Science

Event location: Zürich CH

ISBN: 978-3-319-10592-5

URI: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2014/Placht14-RRC.pdf

DOI: 10.1007/978-3-319-10593-2_50

Abstract

We present a new checkerboard detection algorithm which is able to detect checkerboards at extreme poses, or checkerboards which are highly distorted due to lens distortion even on low-resolution images. On the detected pattern we apply a surface fitting based subpixel refinement specifically tailored for checkerboard X-junctions. Finally, we investigate how the accuracy of a checkerboard detector affects the overall calibration result in multi-camera setups. The proposed method is evaluated on real images captured with different camera models to show its wide applicability. Quantitative comparisons to OpenCV's checkerboard detector show that the proposed method detects up to 80% more checkerboards and detects corner points more accurately, even under strong perspective distortion as often present in wide baseline stereo setups. © 2014 Springer International Publishing.

Authors with CRIS profile

How to cite

APA:

Placht, S., Fürsattel, P., Assoumou Mengue, E., Hofmann, H., Schaller, C., Balda, M., & Angelopoulou, E. (2014). ROCHADE: Robust Checkerboard Advanced Detection for Camera Calibration. In Lecture Notes in Computer Science (pp. 766-779). Zürich, CH: Heidelberg: Springer.

MLA:

Placht, Simon, et al. "ROCHADE: Robust Checkerboard Advanced Detection for Camera Calibration." Proceedings of the Computer Vision - ECCV 2014, Zürich Heidelberg: Springer, 2014. 766-779.

BibTeX: Download