Dynamic baseline stereo vision-based cooperative target tracking

Aamir Ahmad, Eugen Ruff, Heinrich Bulthoff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


In this article we present a new method for multi-robot cooperative target tracking based on dynamic baseline stereo vision. The core novelty of our approach includes a computationally light-weight scheme to compute the 3D stereo measurements that exactly satisfy the epipolar constraints and a covariance intersection (CI)-based method to fuse the 3D measurements obtained by each individual robot. Using CI we are able to systematically integrate the robot localization uncertainties as well as the uncertainties in the measurements generated by the monocular camera images from each individual robot into the resulting stereo measurements. Through an extensive set of simulation and real robot results we show the robustness and accuracy of our approach with respect to ground truth. The source code related to this article is publicly accessible on our website and the datasets are available on request.

Original languageEnglish
Title of host publicationFUSION 2016 - 19th International Conference on Information Fusion, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages7
ISBN (Electronic)9780996452748
Publication statusPublished - 2016 Aug 1
Externally publishedYes
Event19th International Conference on Information Fusion, FUSION 2016 - Heidelberg, Germany
Duration: 2016 Jul 52016 Jul 8


Other19th International Conference on Information Fusion, FUSION 2016


  • cooperative target tracking
  • cooperative visual perception
  • dynamic baseline stereo vision
  • multi robot systems
  • multiple flying robots

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing


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