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Monocular VO Based on Deep Siamese Convolutional Neural Network
Joint Authors
Ding, Fuguang
Zhou, Jiajia
Wang, Hongjian
Xiao, Yao
Ban, Xicheng
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-03-28
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Deep learning-based visual odometry systems have shown promising performance compared with geometric-based visual odometry systems.
In this paper, we propose a new framework of deep neural network, named Deep Siamese convolutional neural network (DSCNN), and design a DL-based monocular VO relying on DSCNN.
The proposed DSCNN-VO not only considers positive order information of image sequence but also focuses on the reverse order information.
It employs supervised data-driven training without relying on any modules in traditional visual odometry algorithm to make the DSCNN to learn the geometry information between consecutive images and estimate a six-DoF pose and recover trajectory using a monocular camera.
After the DSCNN is trained, the output of DSCNN-VO is a relative pose.
Then, trajectory is recovered by translating the relative pose to the absolute pose.
Finally, compared with other DL-based VO systems, we demonstrate the proposed DSCNN-VO achieve a more accurate performance in terms of pose estimation and trajectory recovering through experiments.
Meanwhile, we discuss the loss function of DSCNN and find a best scale factor to balance the translation error and rotation error.
American Psychological Association (APA)
Wang, Hongjian& Ban, Xicheng& Ding, Fuguang& Xiao, Yao& Zhou, Jiajia. 2020. Monocular VO Based on Deep Siamese Convolutional Neural Network. Complexity،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1142870
Modern Language Association (MLA)
Wang, Hongjian…[et al.]. Monocular VO Based on Deep Siamese Convolutional Neural Network. Complexity No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1142870
American Medical Association (AMA)
Wang, Hongjian& Ban, Xicheng& Ding, Fuguang& Xiao, Yao& Zhou, Jiajia. Monocular VO Based on Deep Siamese Convolutional Neural Network. Complexity. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1142870
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142870