ROCHADE: Robust Checkerboard Advanced Detection for Camera Calibration
Author(s): Placht S, Fürsattel P, Assoumou Mengue E, Hofmann H, Schaller C, Balda M, Angelopoulou E
Edition name or number: 1
Title edited volumes: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publishing place: Heidelberg
Publication year: 2014
Conference Proceedings Title: Lecture Notes in Computer Science
Pages range: 766-779
Event: Computer Vision - ECCV 2014
Event location: Zürich
Start date of the event: 06/09/2014
End date of the event: 12/09/2014
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.
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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). 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.