Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 12
3821-3827,3833

Semantic SLAM based on dynamic object tracking

Liu Jiaqi
Gao Yongbin
Jiang Xiaoyan
Fang Zhijun
School of Electric & Electronic Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
DOI: 10.19734/j.issn.1001-3695.2023.03.0147

Abstract

This paper proposed a semantic SLAM algorithm based on dynamic object tracking to address the issue of decreased localization accuracy in traditional visual SLAM methods due to feature matching errors in dynamic scenes. Based on the classic visual SLAM framework, The algorithm extracted dynamic objects for inter-frame tracking and utilized their pose information to assist the camera's own localization. Firstly, it employed YOLACT, RAFT, and SC-Depth networks in the data preprocessing stage to extract semantic masks, optical flow vectors, and pixel depths from the images. Subsequently, the visual frontend module utilized the extracted information to compute probability maps, employing semantic segmentation masks, motion consistency checks, and occlusion point verification algorithms. These probability maps aided in effectively distinguishing between dynamic and static features in the scene. Then, the bundle adjustment module in the back-end integrated multiple feature constraints derived from object motion to enhance the algorithm's pose estimation performance in dynamic scenes. Finally, comprehensive comparisons and validations were conducted on the dynamic scenes of the KITTI and OMD datasets. The experimental results demonstrate that the proposed algorithm accurately tracks dynamic objects and exhibits robust and accurate localization performance in both indoor and outdoor dynamic scenes.

Foundation Support

国家自然科学基金—民航联合重点项目(U2033218)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.03.0147
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 12
Section: Technology of Graphic & Image
Pages: 3821-3827,3833
Serial Number: 1001-3695(2023)12-048-3821-07

Publish History

[2023-07-05] Accepted Paper
[2023-12-05] Printed Article

Cite This Article

刘家麒, 高永彬, 姜晓燕, 等. 基于动态物体跟踪的语义SLAM [J]. 计算机应用研究, 2023, 40 (12): 3821-3827,3833. (Liu Jiaqi, Gao Yongbin, Jiang Xiaoyan, et al. Semantic SLAM based on dynamic object tracking [J]. Application Research of Computers, 2023, 40 (12): 3821-3827,3833. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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