Extrinsic calibration of multi-modal sensor arrangements with non-overlapping field-of-view

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• 作者：Carolina Raposo ; João Pedro Barreto ; Urbano Nunes
• 关键词：Extrinsic calibration ; Laser ; rangefinder ; Depth camera ; Non ; overlapping FOV ; Mirror
• 刊名：Machine Vision and Applications
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：28
• 期：1-2
• 页码：141-155
• 全文大小：
• 刊物类别：Computer Science
• 刊物主题：Pattern Recognition; Image Processing and Computer Vision; Communications Engineering, Networks;
• 出版者：Springer Berlin Heidelberg
• ISSN：1432-1769
• 卷排序：28

文摘

Several applications in robotics require complex sensor arrangements that must be carefully calibrated, both intrinsically and extrinsically, to allow information fusion and enable the system to function as a whole. These arrangements can combine different sensing modalities—such as color cameras, laser-rangefinders, and depth cameras—in an attempt to obtain richer descriptions of the environment. Finding the location of multi-modal sensors in a common world reference frame is a difficult problem that is largely unsolved whenever sensors observe distinct, disjoint parts of the scene. This article builds on recent results in object pose estimation using mirror reflections to provide an accurate and practical solution for the extrinsic calibration of mixtures of color cameras, LRFs, and depth cameras with non-overlapping field-of-view. The method is able to calibrate any possible sensor combination as far as the setup includes at least one color camera. The technique is tested in challenging situations not covered by the current state-of-the-art, proving to be practical and effective. The calibration software is made available to be freely used by the research community.