Radar-vision fusion-based object detection for abnormal data

Renfei Zheng; Songcan Yu; Junbo Wang

doi:10.1117/12.3025735

6 May 2024 Radar-vision fusion-based object detection for abnormal data

Renfei Zheng, Songcan Yu, Junbo Wang

Proceedings Volume 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023); 131610X (2024) https://doi.org/10.1117/12.3025735
Event: Fourth International Conference on Telecommunications, Optics and Computer Science (TOCS 2023), 2023, Xi’an, China

Abstract

In the field of autonomous driving, 3D object detection plays a crucial role as a key perception module. Radar-vision fusion based object detection refers to the technology of combining radar data and visual data to detect and recognize targets. However, in practical situations, visual data may encounter a series of problems during the data collection process, such as limited field of view, lighting variations, motion blur, etc. To address these issues, in addition to the commonly used techniques for onboard cameras, such as dynamic exposure control and low-light enhancement, this paper proposes a novel radar-vision fusion based object detection framework based on CenterFusion. The framework focuses on the case of dealing with abnormal visual data, and aims to achieve more reliable target detection under various complex environmental conditions by fully exploiting the complementary nature of radar and visual data, and introducing a point cloud feature extraction module and a modal attention mechanism. Finally, comparative experiments are conducted on the nuScenes-mini under different conditions, and the experimental results show that the method proposed in this paper can completely replace CenterFusion in various situations, demonstrating excellent performance.

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

Citation Download Citation

Renfei Zheng, Songcan Yu, and Junbo Wang "Radar-vision fusion-based object detection for abnormal data", Proc. SPIE 13161, Fourth International Conference on Telecommunications, Optics, and Computer Science (TOCS 2023), 131610X (6 May 2024); https://doi.org/10.1117/12.3025735

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
11 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Object detection

Radar

Feature extraction

Point clouds

Data fusion

Image fusion

Feature fusion

Show All Keywords

Keywords/Phrases

Search In:

Publication Years