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Mask R-CNN and Optical Flow Based Method for Detection and Marking of Handball Actions


Pobar, Miran; Ivašić-Kos, Marina
Mask R-CNN and Optical Flow Based Method for Detection and Marking of Handball Actions // 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)
Peking, Kina: IEEE, 2018. str. 1-6 doi:10.1109/cisp-bmei.2018.8633201 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Mask R-CNN and Optical Flow Based Method for Detection and Marking of Handball Actions

Autori
Pobar, Miran ; Ivašić-Kos, Marina

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

Izvornik
2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) / - : IEEE, 2018, 1-6

ISBN
978-1-5386-7604-2

Skup
2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

Mjesto i datum
Peking, Kina, 13-15.10.2018

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Object detectors , sports scenes , Mask R-CNN , optical flow , action recognition database

Sažetak
To build a successful supervised learning model for action recognition a large amount of training data needs to be labeled first. Labeling is normally done manually and it is a tedious and time-consuming task, especially in the case of video footage, when each individual athlete performing a given action should be labeled. To minimize the manual labor, we propose a Mask R-CNN and Optical flow based method to determine the active players who perform a given action among all players presented on the scene. The Mask R-CNN is a deep learning object recognition method used for player detection and optical flow measures player activity. Combining both methods ensures tracking and labeling of active players in handball video sequences. The method was successfully tested on a dataset of handball practice videos recorded in the wild.

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:


  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
  • Scopus


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