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.