Player localization using multiple static cameras for sports visualization

We present a novel approach for robust localization of multiple people observed using multiple cameras. We use this location information to generate sports visualizations, which include displaying a virtual offside line in soccer games, and showing players' positions and motion patterns. Our main contribution is the modeling and analysis for the problem of fusing corresponding players' positional information as finding minimum weight K-length cycles in complete K-partite graphs. To this end, we use a dynamic programming based approach that varies over a continuum of being maximally to minimally greedy in terms of the number of paths explored at each iteration. We present an end-to-end sports visualization framework that employs our proposed algorithm-class. We demonstrate the robustness of our framework by testing it on 60,000 frames of soccer footage captured over 5 different illumination conditions, play types, and team attire.