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

PublisherSpringer

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

DOIhttps://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.



Last updated on 2024-26-11 at 23:40