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Robust and efficient edge-based visual odometry

文献类型：期刊论文

作者Yan, Feihu1; Li, Zhaoxin2; Zhou, Zhong1
刊名COMPUTATIONAL VISUAL MEDIA
出版日期2022-03-07
页码15
关键词visual odometry (VO) edge structure distance transform low-texture
ISSN号2096-0433
DOI10.1007/s41095-021-0251-7
英文摘要Visual odometry, which aims to estimate relative camera motion between sequential video frames, has been widely used in the fields of augmented reality, virtual reality, and autonomous driving. However, it is still quite challenging for state-of-the-art approaches to handle low-texture scenes. In this paper, we propose a robust and efficient visual odometry algorithm that directly utilizes edge pixels to track camera pose. In contrast to direct methods, we choose reprojection error to construct the optimization energy, which can effectively cope with illumination changes. The distance transform map built upon edge detection for each frame is used to improve tracking efficiency. A novel weighted edge alignment method together with sliding window optimization is proposed to further improve the accuracy. Experiments on public datasets show that the method is comparable to state-of-the-art methods in terms of tracking accuracy, while being faster and more robust.
资助项目National Key R&D Program of China[2018YFB2100601] ; National Natural Science Foundation of China[61872024] ; National Natural Science Foundation of China[61702482]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000765643300001
出版者SPRINGERNATURE
源URL[http://119.78.100.204/handle/2XEOYT63/18954]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Zhou, Zhong
作者单位1.Beihang Univ, State Key Lab Virtual Real Technol & Syst, Beijing 100191, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Yan, Feihu,Li, Zhaoxin,Zhou, Zhong. Robust and efficient edge-based visual odometry[J]. COMPUTATIONAL VISUAL MEDIA,2022:15.
APA Yan, Feihu,Li, Zhaoxin,&Zhou, Zhong.(2022).Robust and efficient edge-based visual odometry.COMPUTATIONAL VISUAL MEDIA,15.
MLA Yan, Feihu,et al."Robust and efficient edge-based visual odometry".COMPUTATIONAL VISUAL MEDIA (2022):15.

入库方式： OAI收割

来源：计算技术研究所

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