3D fully convolutional network for vehicle detection in point cloud

2D fully convolutional network has been recently successfully applied to the object detection problem on images. In this paper, we extend the fully convolutional network based detection techniques to 3D and apply it to point cloud data. The proposed approach is verified on the task of vehicle detect...

Full description

Saved in:
Bibliographic Details
Published in2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) pp. 1513 - 1518
Main Author Bo Li
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2017
Subjects
Laser radar
Machine learning
Object detection
Three-dimensional displays
Two dimensional displays
Vehicle detection
Online AccessGet full text

Cover

More Information
Summary:2D fully convolutional network has been recently successfully applied to the object detection problem on images. In this paper, we extend the fully convolutional network based detection techniques to 3D and apply it to point cloud data. The proposed approach is verified on the task of vehicle detection from lidar point cloud for autonomous driving. Experiments on the KITTI dataset shows significant performance improvement over the previous point cloud based detection approaches.
ISSN:2153-0866
DOI:10.1109/IROS.2017.8205955