Various autonomous or assisted driving strategies have been facilitated through the
accurate and reliable perception of the environment around a vehicle. Among the commonly …

Multi-object tracking (MOT) aims to associate target objects across video frames in order to
obtain entire moving trajectories. With the advancement of deep neural networks and the …

Multi-Objective Multi-Camera Tracking (MOMCT) is aimed at locating and identifying
multiple objects from video captured by multiple cameras. With the advancement of …

Abstract Multi-Target Multi-Camera Tracking has a wide range of applications and is the
basis for many advanced inferences and predictions. This paper describes our solution to …

Radar is usually more robust than the camera in severe driving scenarios, eg, weak/strong
lighting and bad weather. However, unlike RGB images captured by a camera, the semantic …

Radar has long been a common sensor on autonomous vehicles for obstacle ranging and
speed estimation. However, as a robust sensor to all-weather conditions, radar's capability …

Abstract Multi-camera Multi-Object Tracking has drawn significant attention in recent years
due to its critical role in surveillance analytics and related fields. Various challenges …

In this paper, we propose a novel framework for multi-target multi-camera tracking (MTMCT)
of vehicles based on metadata-aided re-identification (MA-ReID) and the trajectory-based …

With the demands of the intelligent city and city-scale traffic management, city-scale multi-
camera vehicle tracking (MCVT) has become a vital problem. The MCVT is challenging due …

Abstract Multi-Camera Multi-Vehicle Tracking (MCMVT) is an essential task in the field of city-
scale traffic management, which usually consists of three sub-tasks: object detection and re …