An Improved Fast Visual Odometry Based on Semi-probabilistic Trimmed ICP
Authors: 
Hong Zhang, Shiqiang HuAuthors Info & Claims
Hong Zhang, Shiqiang HuAuthors Info & ClaimsPages 27 - 32
Abstract
This paper presents an improved method for Fast Visual Odometry estimation from a Kinect-style RGB-D camera. In order to improve the accuracy and robustness of Fast Visual Odometry, we propose a modified ICP algorithm called Semi-probabilistic Trimmed ICP and a transform strategy between frame-to-model approach and frame-to-frame approach. An overlap parameter is computed to reject outlier before the registration. And if it comes to a occasional large camera motion, we skip the current frame and compute a coarse initial guess by the RANSAC algorithm between the next frame and the previous frame, finally refine the pose of camera by the original ICP. The evaluation on TUM RGB-D benchmark shows that Our Visual Odometry outperforms state-of-the-art in certain scenarios like a small-scale camera motion and it's capable of dealing with an occasional large camera motion.
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- An Improved Fast Visual Odometry Based on Semi-probabilistic Trimmed ICP
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Published In
June 2018
126 pages
ISBN:9781450364850
DOI:10.1145/3234664
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In-Cooperation
- Shanghai Jiao Tong University: Shanghai Jiao Tong University
- Xi'an Jiaotong-Liverpool University: Xi'an Jiaotong-Liverpool University
- Chinese Academy of Sciences
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Association for Computing Machinery
New York, NY, United States
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Published: 22 June 2018
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HPCCT 2018
HPCCT 2018: 2018 2nd High Performance Computing and Cluster Technologies Conference
June 22 - 24, 2018
Beijing, China
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