Paper Info
Title
An Improved Fast Visual Odometry Based On Semi-Probabilistic Trimmed Icp
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.
Year
DOI
Venue
2018
10.1145/3234664.3234666
PROCEEDINGS OF THE 2018 2ND HIGH PERFORMANCE COMPUTING AND CLUSTER TECHNOLOGIES CONFERENCE (HPCCT 2018)
Keywords
DocType
Citations 
Visual odometry, semi-probabilistic trimmed-ICP, frame-to-model, frame-to-frame
Conference
0
PageRank 
References 
Authors
0.34
10
2
Name
Order
Citations
PageRank
Zhang Hong1183.74
Shiqiang Hu25310.05