Extended Object Tracking: Introduction, Overview and Applications

By Karl Granström, Marcus Baum. arXiv.org, 2016

432 citations recorded by the source corpus.

This article provides an elaborate overview of current research in extended object tracking. We provide a clear definition of the extended object tracking problem and discuss its delimitation to other types of object tracking. Next, different aspects of extended object modelling are extensively discussed. Subsequently, we give a tutorial introduction to two basic and well used extended object tracking approaches - the random matrix approach and the Kalman filter-based approach for star-convex shapes. The next part treats the tracking of multiple extended objects and elaborates how the large number of feasible association hypotheses can be tackled using both Random Finite Set (RFS) and Non-RFS multi-object trackers. The article concludes with a summary of current applications, where four example applications involving camera, X-band radar, light detection and ranging (lidar), red-green-blue-depth (RGB-D) sensors are highlighted.

Subfields: Artificial Intelligence, Geometry and Topology, Media Technology

View Paper: https://www.semanticscholar.org/paper/b1976394abf58b8f92075dced185c8d60d5dbdca

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

  1. Gonzalo Seco-Granados
  2. Henk Wymeersch
  3. Davide Dardari

Citations in the corpus