Virtual Validation of a Multi-Object Tracker with Intercamera Tracking for Automotive Fisheye Based Surround View Systems

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.