A4 Vertaisarvioitu artikkeli konferenssijulkaisussa
Real-Time Swimmer Tracking on Sparse Camera Array
Tekijät: Paavo Nevalainen, M. Hashem Haghbayan, Antti Kauhanen, Jonne Pohjankukka, Mikko-Jussi Laakso, Jukka Heikkonen
Toimittaja: Ana Fred, Maria De Marsico, Gabriella Sanniti di Baja
Konferenssin vakiintunut nimi: International Conference on Pattern Recognition Applications and Methods
Kustantaja: Springer
Kustannuspaikka: Chamberra
Julkaisuvuosi: 2017
Kokoomateoksen nimi: Pattern Recognition Applications and Methods: 5th International Conference, ICPRAM 2016, Rome, Italy, February 24-26, 2016, Revised Selected Papers
Sarjan nimi: Lecture Notes in Computer Science
Vuosikerta: 10163
Aloitussivu: 156
Lopetussivu: 174
Sivujen määrä: 19
ISBN: 978-3-319-53374-2
eISBN: 978-3-319-53375-9
ISSN: 0302-9743
DOI: https://doi.org/10.1007/978-3-319-53375-9_9
Verkko-osoite: 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.