3D modeling of channel scene based on multi-eye vision

Qingfeng Wen; Jieyin Nan; An Chang; Xuegang Li; Longji Li; Songbo Wang

doi:10.1117/12.2661043

3 February 2023 3D modeling of channel scene based on multi-eye vision

Qingfeng Wen, Jieyin Nan, An Chang, Xuegang Li, Longji Li, Songbo Wang

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 125111M (2023) https://doi.org/10.1117/12.2661043
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

Aiming at the fact that the current channel scene reconstruction method cannot meet the requirements of depth recovery, this time, the research on the 3D modeling method of channel scene based on multi-eye vision is carried out. According to the image's intersection ratio and the intersection point's position, the orientation of the collected image in the transmission channel scene is judged, the marker points are identified, and the YOLOv3 model is used to match the image characteristics of the transmission channel scene. In the matched image, the point closest to the image point of the same name on each ray of the multi-eye vision area is determined as the optimal solution of spatial point coordinates, and the 3D modeling of the channel scene is completed. The test results show that the design method uses multi-eye image data to perform 3D restoration of the channel scene, the ranging error does not exceed 2m, the RMSE does not exceed 0.1, and a good modeling effect is obtained. The design method improves the adaptability of 3D modeling to complex scene environments in identifying and detecting hidden dangers in transmission channels.

Citation Download Citation

Qingfeng Wen, Jieyin Nan, An Chang, Xuegang Li, Longji Li, and Songbo Wang "3D modeling of channel scene based on multi-eye vision", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 125111M (3 February 2023); https://doi.org/10.1117/12.2661043

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