Virtual validation of a multi-object tracker with intercamera tracking for automotive fisheye based surround view systems
Egileak: Guillem Delgado Gonzalo
Data: 11.07.2022
Abstract
Surround view systems are becoming more and more important in Autonomous Driving and Advanced Driver Assistance Systems where multiple perception tasks have been developed in order to solve the needs in this field. However, there is a lack of literature for multi-object trackers that deals with multiple cameras in automotive setups. In this paper, we propose a system to tackle multi-object tracking with inter-camera object identification using fisheye cameras covering a 360º view in real time. We provide results from a custom ground truth annotated sequence using CARLA simulator.
BIB_text
author = {Guillem Delgado Gonzalo},
title = {Virtual validation of a multi-object tracker with intercamera tracking for automotive fisheye based surround view systems},
keywds = {
deep learning, autonomous driving, object detection, surround-view systems, multi-object tracking, intercamera tracking, carla simulator
}
abstract = {
Surround view systems are becoming more and more important in Autonomous Driving and Advanced Driver Assistance Systems where multiple perception tasks have been developed in order to solve the needs in this field. However, there is a lack of literature for multi-object trackers that deals with multiple cameras in automotive setups. In this paper, we propose a system to tackle multi-object tracking with inter-camera object identification using fisheye cameras covering a 360º view in real time. We provide results from a custom ground truth annotated sequence using CARLA simulator.
}
isbn = {978-1-6654-7822-9},
date = {2022-07-11},
}