The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLIII-B3-2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-599-2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-599-2020
21 Aug 2020
 | 21 Aug 2020

AUTOMATIC TRAFFIC SIGN DETECTION AND RECOGNITION USING MOBILE LIDAR DATA WITH DIGITAL IMAGES

H. Guan, Y. Yu, D. Li, and J. Li

Keywords: mobile LiDAR, images, traffic sign, capsule convolutional networks, high-order capsule features

Abstract. This paper presents a traffic sign detection and recognition method from mobile LiDAR data and digital images for intelligent transportation-related applications. The traffic sign detection and recognition method includes two steps: traffic sign interest regions are first extracted from mobile LiDRA data. Next, traffic signs are identified from digital images simultaneously collected from the multi-sensor mobile LiDAR systems via a convolutional capsule network model. The experimental results demonstrate that the proposed method obtains a promising, reliable, and high performance in both detecting traffic signs in 3-D point clouds and recognizing traffic signs on 2-D images.