  Multi Object Tracking (MOT) in ice hockey pursues the combined task of
localizing and associating players across a given sequence to maintain their
identities. Tracking players from monocular broadcast feeds is an important
computer vision problem offering various downstream analytics and enhanced
viewership experience. However, existing trackers encounter significant
difficulties in dealing with occlusions, blurs, and agile player movements
prevalent in telecast feeds. In this work, we propose a novel tracking approach
by formulating MOT as a bipartite graph matching problem infused with
homography. We disentangle the positional representations of occluded and
overlapping players in broadcast view, by mapping their foot keypoints to an
overhead rink template, and encode these projected positions into the graph
network. This ensures reliable spatial context for consistent player tracking
and unfragmented tracklet prediction. Our results show considerable
improvements in both the IDsw and IDF1 metrics on the two available broadcast
ice hockey datasets.
