Virtual tracking shots for sports analysis

Abstract

Reviewing athletic performance is a critical part of modern sports training, but snapshots only showing part of a course or exercise can be misleading, while travelling cameras are expensive. In this paper we describe a system merging the output of many autonomous inexpensive camera nodes distributed around a course to reliably synthesize tracking shots of multiple athletes training concurrently. Issues such as uncontrolled lighting, athlete occlusions and overtaking/pack-motion are dealt with, as is compensating for the quirks of cheap image sensors. The resultant system is entirely automated, inexpensive, scalable and provides output in near real-time, allowing coaching staff to give immediate and relevant feedback on a performance. Requiring no alteration to existing training exercises has boosted the system's uptake by coaches, with over 100,000 videos recorded to date.