Tracking for Context Extraction in Athletic Events

Personalisation of large scale athletic events requires camera-specific annotations to provide for reasoning about incidents being best viewed by specific cameras. This needs an automatic system for annotating athletes on the video streams, to be achieved by the use of person trackers. In this paper we present a novel approach towards combining scene segmentation, motion outliers, face and bib tracks into body hypotheses and tracking them across time. Preliminary evaluation results demonstrate the potential of the proposed approach.