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Detection of the leading player in handball scenes using Mask R-CNN and STIPS


Pobar, Miran; Ivašić-Kos, Marina
Detection of the leading player in handball scenes using Mask R-CNN and STIPS // Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018) / Verikas, A. ; Nikolaev, D.P. ; Radeva, P. ; Zhou, J. (ur.).
Muenchen: SPIE, 2018. 110411V, 8 doi:10.1117/12.2522668 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Detection of the leading player in handball scenes using Mask R-CNN and STIPS

Autori
Pobar, Miran ; Ivašić-Kos, Marina

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018) / Verikas, A. ; Nikolaev, D.P. ; Radeva, P. ; Zhou, J. - Muenchen : SPIE, 2018

ISBN
978-151062748-2

Skup
11th International Conference on Machine Vision, ICMV 2018

Mjesto i datum
Muenchen, Njemačka, 1.-3.11.2018.

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Object detectors ; handball scenes ; Mask R-CNN ; spatiotemporal interest point – STIP tracking ; attention

Sažetak
In team sports scenes, recorded during training and lessons, it is common to have many players on the court, each with his own ball performing different actions. Our goal is to detect all players in the handball court and determine the leading player who performs the given handball technique such as a shooting at the goal, catching a ball or dribbling. This is a very challenging task for which, apart from an accurate object detector that is able to deal with cluttered scenes with many objects, partially occluded and with bad illumination, additional information is needed to determine the leading player. Therefore, we propose a leading player detector method combining the Mask R-CNN object detector and spatiotemporal interest points, referred to as MR-CNN+STIPs. The performance of the proposed leading player detector is evaluated on a custom sports video dataset acquired during handball training lessons. The performance of the detector in different conditions will be discussed.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Projekt / tema
HRZZ-IP-2016-06-8345 - Automatsko raspoznavanje akcija i aktivnosti u multimedijalnom sadržaju iz domene sporta (Marina Ivašić-Kos, )

Ustanove
Sveučilište u Rijeci - Odjel za informatiku

Časopis indeksira:


  • Scopus


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