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Robust Multi-Person Tracking from Moving Platforms Ess, Andreas Schindler, Konrad Leibe, Bastian van Gool, Luc Pedestrian detection tracking Mobile vision In this paper, we address the problem of multi-person tracking in busy pedestrian zones, using a stereo rig mounted on a mobile platform. The complexity of the problem calls for an integrated solution, which extracts as much visual information as possible and combines it through cognitive feedback. We propose such an approach, which jointly estimates camera position, stereo depth, object detection, and tracking. We model the interplay between these components using a graphical model. Since the model has to incorporate object-object interactions, and temporal links to past frames, direct inference is intractable. We therefore propose a two-stage procedure: for each frame we first solve a simplified version of the model (disregarding interactions and temporal continuity) to estimate the scene geometry and an overcomplete set of object detections. Conditioned on these results, we then address object interactions, tracking, and prediction in a second step. The approach is experimentally evaluated on several long and difficult video sequences from busy inner-city locations. Our results show that the proposed integration makes it possible to deliver stable tracking performance in scenes of realistic complexity. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Andreas Ess and Konrad Schindler and Bastian Leibe and Luc van Gool 2008 Is Part Of Dagstuhl Seminar Proceedings, Volume 8091, Logic and Probability for Scene Interpretation (2008) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.08091.13 urn:nbn:de:0030-drops-16173 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08091.13 eng https://creativecommons.org/licenses/by/4.0/legalcode