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Taking Mobile Multi-object Tracking to the Next Level: People, Unknown Objects, and Carried Items

  • Dennis Mitzel
  • Bastian Leibe
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7576)

Abstract

In this paper, we aim to take mobile multi-object tracking to the next level. Current approaches work in a tracking-by-detection framework, which limits them to object categories for which pre-trained detector models are available. In contrast, we propose a novel tracking-before-detection approach that can track both known and unknown object categories in very challenging street scenes. Our approach relies on noisy stereo depth data in order to segment and track objects in 3D. At its core is a novel, compact 3D representation that allows us to robustly track a large variety of objects, while building up models of their 3D shape online. In addition to improving tracking performance, this representation allows us to detect anomalous shapes, such as carried items on a person’s body. We evaluate our approach on several challenging video sequences of busy pedestrian zones and show that it outperforms state-of-the-art approaches.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dennis Mitzel
    • 1
  • Bastian Leibe
    • 1
  1. 1.Computer Vision GroupRWTH Aachen UniversityGermany

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