@article{ref1,
title="Analysis and synthesis of traffic scenes from road image sequences",
journal="Sensors (Basel)",
year="2020",
author="Yuan, Sheng and Chen, Yuting and Huo, Huihui and Zhu, Li",
volume="20",
number="23",
pages="e6939-e6939",
abstract="Traffic scene construction and simulation has been a hot topic in the community of intelligent transportation systems. In this paper, we propose a novel framework for the analysis and synthesis of traffic elements from road image sequences. The proposed framework is composed of three stages: traffic elements detection, road scene inpainting, and road scene reconstruction. First, a new bidirectional single shot multi-box detector (BiSSD) method is designed with a global context attention mechanism for traffic elements detection. After the detection of traffic elements, an unsupervised CycleGAN is applied to inpaint the occlusion regions with optical flow. The high-quality inpainting images are then obtained by the proposed image inpainting algorithm. Finally, a traffic scene simulation method is developed by integrating the foreground and background elements of traffic scenes. The extensive experiments and comparisons demonstrate the effectiveness of the proposed framework.<p /> <p>Language: en</p>",
language="en",
issn="1424-8220",
doi="10.3390/s20236939",
url="http://dx.doi.org/10.3390/s20236939"
}