Robust Tracking of Spatial Related Components
This paper introduces a hierarchical approach for multicomponent tracking, where the object-to-be-tracked is modeled as a group of spatial related parts. We propose to use a robust particle filtering framework for tracking the individual components and outline how the spatial coherency between the parts can be efficiently integrated by analyzing a two-level hierarchy of particle filters. Including spatial information allows to handle common tracking problems like occlusions, clutter or blur. Furthermore, the dynamic calculation of particle set uncertainties allows a dynamic adaption of stiffness values for the spatial model to e. g. force occluded parts to stay in spatial relation. The experimental section proves the robustness of the proposed tracker on challenging sequences e.g. VIVID-PETS database.
- Mauthner T. and Donoser M. and Bischof H. (2008): Robust Tracking of Spatial Related Components, Proceedings ICPR
Example videos show tracking results on multi-object, non-rigid or partial-occlusion scenes of standard datasets and some additional selected challenging videos.