Tutorial: Extended Object Tracking and Sensor Fusion

Organizers

  • Karl Granström, Chalmers University of Technology, Sweden
  • Marcus Baum, University of Goettingen, Germany
  • Jens Honer, Valeo Schalter & Sensoren, Bietigheim-Bissingen, Germany
  • Stephan Reuter (2016/17)

Keywords

Sensor fusion, multi-object-tracking, extended objects, data association, clustering, radar, lidar, vision, autonomous vehicles, environment perception

Description

Environment perception for autonomous vehicles involves the important tasks of detecting, classifying and tracking all objects of interests in the vicinity of the vehicle, such as vehicles, pedestrians, and bicyclists. Solving these tasks accurately and robustly is paramount for the safe operation of the vehicle. In this context, this tutorial provides an overview of sensor fusion and multi-object tracking techniques. The focus lies on high-resolution sensors (e.g., lidar, radar, and camera devices) that give rise to multiple detections per object. In the first part of the tutorial, the modeling of different object and measurement types is discussed and suitable (single) object tracking approaches are presented. The second part of the tutorial introduces recent data association and clustering methods for tracking multiple objects. Finally, the last part of the tutorial demonstrates applications and discusses pitfalls of these approaches in real-world scenarios.

Since 2016, the tutorial has been organized eight times at international conferences such as the International Conference on Information Fusion and IEEE Intelligent Vehicles Symposium.

Upcoming Tutorials in 2020

  • TBA

Slides

The username for the slides is "tutorial". Please contact Marcus Baum for the password.
Title Presenter Slides
Introduction all PDF
Motivation and Applications Jens Honer PDF
Single Extended Object Tracking Marcus Baum PDF
Multiple Extended Object Tracking Karl Granström PDF

Overview Paper

The tutorial is based on the following overview article that is available online:

Extended Object Tracking: Introduction, Overview and Applications
K. Granström, M. Baum, and S. Reuter
ISIF Journal of Advances in Information Fusion, vol. 12, no. 2, Dec. 2017.

Additional Material

Source Code

Further Literature

Previous Tutorials