Dynamic visual SLAM system based on weighted static features

Xinyu Hu; Qimin Li

doi:10.1117/12.2684168

1 August 2023 Dynamic visual SLAM system based on weighted static features

Xinyu Hu, Qimin Li

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 1275407 (2023) https://doi.org/10.1117/12.2684168
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

Existing visual simultaneous localization and mapping (SLAM) systems usually assume that the environment is static, therefore when many mature visual SLAM algorithms are applied to dynamic scenes, the pose errors estimated by the system will increase sharply due to the interference of dynamic objects. To address this problem, this paper proposes a robust visual SLAM system based on ORB-SLAM2 using static features and realizes a two-stage tracking from coarse to fine to improve the system localization accuracy in a dynamic environment. The proposed method uses the yolov5-seg network to implement a semantic thread, then combines semantic prior information and geometric information to accurately extract dynamic feature points, and realizes pose optimization based on the static weight of feature points. In addition, an improved keyframe selection strategy is implemented. Experiments on the public TUM dynamic datasets show that the proposed algorithm performs well on most dynamic datasets, has a great improvement compared with the ORB-SLAM2, and achieves the same accuracy as other advanced dynamic SLAM systems.

Citation Download Citation

Xinyu Hu and Qimin Li "Dynamic visual SLAM system based on weighted static features", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 1275407 (1 August 2023); https://doi.org/10.1117/12.2684168

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available