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Benefit of large field-of-view cameras for visual odometry


Zhang, Zichao; Rebecq, Henri; Forster, Christian; Scaramuzza, Davide (2016). Benefit of large field-of-view cameras for visual odometry. In: IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 16 May 2016 - 21 May 2016, 801-808.

Abstract

The transition of visual-odometry technology from research demonstrators to commercial applications naturally raises the question: “what is the optimal camera for vision-based
motion estimation?” This question is crucial as the choice of camera has a tremendous impact on the robustness and accuracy of the employed visual odometry algorithm. While many properties of a camera (e.g. resolution, frame-rate, global-shutter/rolling-shutter) could be considered, in this work we focus on evaluating the impact of the camera field-of-view (FoV) and optics (i.e., fisheye or catadioptric) on the quality of the motion estimate. Since the motion-estimation performance depends highly on the geometry of the scene and the motion of the camera, we analyze two common operational environments in mobile robotics: an urban environment and an indoor scene. To confirm the theoretical observations, we implement a state-of-the-art VO pipeline that works with large FoV fisheye and catadioptric cameras. We evaluate the proposed VO pipeline in
both synthetic and real experiments. The experiments point out that it is advantageous to use a large FoV camera (e.g., fisheye or catadioptric) for indoor scenes and a smaller FoV for urban
canyon environments.

Abstract

The transition of visual-odometry technology from research demonstrators to commercial applications naturally raises the question: “what is the optimal camera for vision-based
motion estimation?” This question is crucial as the choice of camera has a tremendous impact on the robustness and accuracy of the employed visual odometry algorithm. While many properties of a camera (e.g. resolution, frame-rate, global-shutter/rolling-shutter) could be considered, in this work we focus on evaluating the impact of the camera field-of-view (FoV) and optics (i.e., fisheye or catadioptric) on the quality of the motion estimate. Since the motion-estimation performance depends highly on the geometry of the scene and the motion of the camera, we analyze two common operational environments in mobile robotics: an urban environment and an indoor scene. To confirm the theoretical observations, we implement a state-of-the-art VO pipeline that works with large FoV fisheye and catadioptric cameras. We evaluate the proposed VO pipeline in
both synthetic and real experiments. The experiments point out that it is advantageous to use a large FoV camera (e.g., fisheye or catadioptric) for indoor scenes and a smaller FoV for urban
canyon environments.

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3 citations in Web of Science®
7 citations in Scopus®
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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Event End Date:21 May 2016
Deposited On:12 Aug 2016 07:39
Last Modified:08 Dec 2017 20:09
Publisher:Institute of Electrical and Electronics Engineers
Series Name:IEEE International Conference on Robotics and Automation. Proceedings
ISSN:1050-4729
Publisher DOI:https://doi.org/10.1109/ICRA.2016.7487210
Related URLs:http://www.icra2016.org/ (Organisation)
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7478842 (Publisher)
Other Identification Number:merlin-id:13324

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