Real-Time Swimmer Tracking on Sparse Camera Array
: Paavo Nevalainen, M. Hashem Haghbayan, Antti Kauhanen, Jonne Pohjankukka, Mikko-Jussi Laakso, Jukka Heikkonen
: Ana Fred, Maria De Marsico, Gabriella Sanniti di Baja
: International Conference on Pattern Recognition Applications and Methods
Publisher: Springer
: Chamberra
: 2017
: Pattern Recognition Applications and Methods: 5th International Conference, ICPRAM 2016, Rome, Italy, February 24-26, 2016, Revised Selected Papers
: Lecture Notes in Computer Science
: 10163
: 156
: 174
: 19
: 978-3-319-53374-2
: 978-3-319-53375-9
: 0302-9743
DOI: https://doi.org/10.1007/978-3-319-53375-9_9
: https://link.springer.com/chapter/10.1007/978-3-319-53375-9_9
A swimmer detection and tracking is an essential first step in a video-based athletics performance analysis. A real-time algorithm is presented, with the following capabilities: performing the planar projection of the image, fading the background to protect the intimacy of other swimmers, framing the swimmer at a specific swimming lane, and eliminating the redundant video stream from idle cameras. The generated video stream is a basis for further analysis at the batch-mode. The geometric video transform accommodates a sparse camera array and enables geometric observations of swimmer silhouette. The tracking component allows real-time feedback and combination of different video streams to a single one. Swimming cycle registration algorithm based on markerless tracking is presented. The methodology allows unknown camera positions and can be installed in many types of public swimming pools.
athletics, camera calibration, swimming