Add to ORKGAbstract- In this contribution we apply the proba-bility hypothesis density (PHD) filter algorithm for joint tracking of an unknown varying number of targets to automotive environment sensing systems. We use data from a vision and a lidar sensor as well as the vehicle ESP system. After deriving a method to parametrise the algorithm systematically from de-tection performance statistics we proof the applica-bility of the method for automotive tracking based on real sensor data
The problem of multi-object tracking with sensor networks is studied using the probability hypothesi...
This thesis considers two different research problems; one concerned with the issue of tracking vehi...
Environment perception is an important aspect of modern automated systems. The perception consists o...
Mapping stationary objects is essential for autonomous vehicles and many autonomous functions in veh...
Mapping stationary objects is essential for autonomous vehicles and many autonomous functions in veh...
Abstract – When tracking a large number of targets, it is often computationally expensive to represe...
In the past decade, the developments of vehicle detection have been significantly improved. By utili...
Novel advance driver assistance systems, such as emergency braking and adaptive cruise control requi...
Vehicle detection is one of the classical application among the Advance Driver Assistance Systems (...
The probability hypothesis density (PHD) methodology is widely used by the research community for th...
Abstract—In multi-target tracking, the discrepancy between the nominal and the true values of the mo...
Interactive robots such as self-driving cars require accurate hardware and methods to locate relevan...
This thesis studies the problem of tracking in the setting of an automotive safety system. In partic...
The probability hypothesis density (<i>PHD</i>) methodology is widely used by the research community...
This article presents a probabilistic method for vehicle tracking using a sensor composed of both a ...
The problem of multi-object tracking with sensor networks is studied using the probability hypothesi...
This thesis considers two different research problems; one concerned with the issue of tracking vehi...
Environment perception is an important aspect of modern automated systems. The perception consists o...
Mapping stationary objects is essential for autonomous vehicles and many autonomous functions in veh...
Mapping stationary objects is essential for autonomous vehicles and many autonomous functions in veh...
Abstract – When tracking a large number of targets, it is often computationally expensive to represe...
In the past decade, the developments of vehicle detection have been significantly improved. By utili...
Novel advance driver assistance systems, such as emergency braking and adaptive cruise control requi...
Vehicle detection is one of the classical application among the Advance Driver Assistance Systems (...
The probability hypothesis density (PHD) methodology is widely used by the research community for th...
Abstract—In multi-target tracking, the discrepancy between the nominal and the true values of the mo...
Interactive robots such as self-driving cars require accurate hardware and methods to locate relevan...
This thesis studies the problem of tracking in the setting of an automotive safety system. In partic...
The probability hypothesis density (<i>PHD</i>) methodology is widely used by the research community...
This article presents a probabilistic method for vehicle tracking using a sensor composed of both a ...
The problem of multi-object tracking with sensor networks is studied using the probability hypothesi...
This thesis considers two different research problems; one concerned with the issue of tracking vehi...
Environment perception is an important aspect of modern automated systems. The perception consists o...