Research on fusion-based deep convolutional networks in 3D object detection

Y. Zhang; C. C. Yue

doi:10.1117/12.2638587

23 May 2022 Research on fusion-based deep convolutional networks in 3D object detection

Y. Zhang, C. C. Yue

Proceedings Volume 12254, International Conference on Electronic Information Technology (EIT 2022); 1225429 (2022) https://doi.org/10.1117/12.2638587
Event: International Conference on Electronic Information Technology (EIT 2022), 2022, Chengdu, China

Abstract

Aiming at the problem that the uniformly sampled point cloud is used for training in the three-dimensional object detection of RGB-D data, the accuracy of the point cloud in the actual scene is reduced, and the PointConv network is proposed to detect the loss of some key point cloud features. Firstly, by generating a 2D area proposal from the image and positioning it in the 3D point cloud data. Secondly, the 2D-driven 3D target detection is realized by the segmentation network based on PointConv and the 3D bounding box evaluation network. At last, evaluated on the KITTI and SUN RGB-D datasets, this method has real-time capabilities and surpasses the current detection levels of DoBEM, MV3D, Mono3D, Frustum PointNets ,and other methods. Experimental results show that compared with the previous state-of-the- art technology, our method improves mAP by 0.5% to 12.4%, and is 1-3 orders of magnitude faster.

Citation Download Citation

Y. Zhang and C. C. Yue "Research on fusion-based deep convolutional networks in 3D object detection", Proc. SPIE 12254, International Conference on Electronic Information Technology (EIT 2022), 1225429 (23 May 2022); https://doi.org/10.1117/12.2638587

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