Sensors, Vol. 20, Pages 6515: Traffic Intersection Re-Identification Using Monocular Camera Sensors

Sensors, Vol. 20, Pages 6515: Traffic Intersection Re-Identification Using Monocular Camera Sensors Sensors doi: 10.3390/s20226515 Authors: Lu Xiong Zhenwen Deng Yuyao Huang Weixin Du Xiaolong Zhao Chengyu Lu Wei Tian Perception of road structures especially the traffic intersections by visual sensors is an essential task for automated driving. However, compared with intersection detection or visual place recognition, intersection re-identification (intersection re-ID) strongly affects driving behavior decisions with given routes, yet has long been neglected by researchers. This paper strives to explore intersection re-ID by a monocular camera sensor. We propose a Hybrid Double-Level re-identification approach which exploits two branches of Deep Convolutional Neural Network to accomplish multi-task including classification of intersection and its fine attributes, and global localization in topological maps. Furthermore, we propose a mixed loss training for the network to learn the similarity of two intersection images. As no public datasets are available for the intersection re-ID task, based on the work of RobotCar, we propose a new dataset with carefully-labeled intersection attributes, which is called “RobotCar Intersection” and covers more than 30,000 images of eight intersections in different seasons and day time. Additionally, we provide another dataset, called “Campus Intersection” consisting o...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research