TVVS: A top-view visualization system from broadcasting soccer video

A holy grail for sports analytics is the top-view visualization of the game. The top-view visualization provides the actual between-player distances as opposed to the between-player distances calculated from the side and/or oblique view of a match. Related work in this area relies on multiple camera installations in the stadium or directly derive the registration map between a broadcasting video and the top-view model. Aberrating the state-of-the-art, a factor theory based approach is presented to derive the top-view visualization of the game from the broadcasting sports video. It is theoretically proved that the proposed factor theory based approach is more efficient than the state-of-the-art approach for the top-view visualization. In addition, as per the proposed approach, a model is presented for the top-view visualization by transforming the broadcasting video into a single and static camera visualization. In order to generate the single-camera visualization, the view of the entire ground is needed which is expressed as a solution to a convex optimization function, devised to explore putative matrix completions. To give pristine empirical evidence, the benchmark dataset is used and a soccer dataset has been introduced towards the end. The proposed top-view approach brings atleast 7% and 10% gains over the state-of-the-art on the benchmark and the proposed dataset respectively.