Visual object tracking for mobile robots based on SAM-TRACK

Yiming Liu; Guowei Zhang

doi:10.1117/12.3026754

27 March 2024 Visual object tracking for mobile robots based on SAM-TRACK

Yiming Liu, Guowei Zhang

Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 131052V (2024) https://doi.org/10.1117/12.3026754
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China

Abstract

The application of visual object tracking SAM-TRACK is widespread. For the problem of robot positioning and navigation, a single laser sensor obtains less information. Adding a depth camera to provide visual information will enhance the robustness of the system. Design a system for visual object tracking based on laser SLAM. Identify and segment targets by clicking, drawing edges, and inputting text, and calculate the target position by comparing the segmentation results with the depth map. At the same time, track the target in real-time to control the robot to ultimately reach the target position. Experiments have shown that multiple input methods can effectively achieve segmentation; By comparing with SiamRPN, it has been proven that the system is more efficient.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yiming Liu and Guowei Zhang "Visual object tracking for mobile robots based on SAM-TRACK", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 131052V (27 March 2024); https://doi.org/10.1117/12.3026754

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