Robust scale initialization for long-range stereo visual odometry

Warren, Michael & Upcroft, Ben (2013) Robust scale initialization for long-range stereo visual odometry. In IROS2013 : IEEE/RSJ International Conference on Intelligent Robots and Systems : New Horizon, 3-8 November 2013, Tokyo Big Sight, Tokyo, Japan.

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Abstract

Achieving a robust, accurately scaled pose estimate in long-range stereo presents significant challenges. For large scene depths, triangulation from a single stereo pair is inadequate and noisy. Additionally, vibration and flexible rigs in airborne applications mean accurate calibrations are often compromised. This paper presents a technique for accurately initializing a long-range stereo VO algorithm at large scene depth, with accurate scale, without explicitly computing structure from rigidly fixed camera pairs. By performing a monocular pose estimate over a window of frames from a single camera, followed by adding the secondary camera frames in a modified bundle adjustment, an accurate, metrically scaled pose estimate can be found. To achieve this the scale of the stereo pair is included in the optimization as an additional parameter. Results are presented both on simulated and field gathered data from a fixed-wing UAV flying at significant altitude, where the epipolar geometry is inaccurate due to structural deformation and triangulation from a single pair is insufficient. Comparisons are made with more conventional VO techniques where the scale is not explicitly optimized, and demonstrated over repeated trials to indicate robustness.

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ID Code: 61675
Item Type: Conference Paper
Refereed: Yes
Keywords: Stereo Vision, Visual Odometry, UAV, Computer Vision, Bundle Adjustment
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 Please consult the authors
Deposited On: 04 Aug 2013 22:15
Last Modified: 05 Aug 2014 20:40

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