This paper presents a novel method for traffic sign detection and visibility evaluation from mobile Light Detection and Ranging (LiDAR) point clouds and the corresponding images. Our algorithm involves two steps. Firstly, a detection algorithm based on high retro-reflectivity of the traffic sign from the MLS point clouds is designed for sign detection in complicated road scenes. To solve the spatial features of traffic signs, we also create geo-referenced relations between traffic signs and roads according to the normal of ground. Secondly, we propose a visibility estimation method to evaluate the visibility level of the traffic sign based on a combination of visual appearance and spatial-related features. The proposed algorithm is validated on a set of transportation-related point-clouds acquired by a RIEGL VMX-450 LiDAR system. The experiment results demonstrate that the efficiency and reliability of the proposed algorithm in detection traffic signs are robust, and also prove the potential of using mobile LiDAR data for traffic sign visibility evaluation.
Using mobile LiDAR point clouds for traffic sign detection and sign visibility estimation
2015-07-01
551908 byte
Conference paper
Electronic Resource
English
AUTOMATED VISIBILITY FIELD EVALUATION OF TRAFFIC SIGN BASED ON 3D LIDAR POINT CLOUDS
DOAJ | 2019
|Traffic Sign Occlusion Detection Using Mobile Laser Scanning Point Clouds
Online Contents | 2017
|Traffic Sign Occlusion Detection Using Mobile Laser Scanning Point Clouds
Online Contents | 2017
|