prikaz prve stranice dokumenta Detection of the leading player in handball scenes using Mask R-CNN and STIPS
  Download
PDF 994.62 KB
Scientific paper - Original scientific paper
Detection of the leading player in handball scenes using Mask R-CNN and STIPS
In: Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018). / Verikas, A.; Nikolaev, D.P.; Radeva, P.; Zhou, J. (Ed.). Society of Photo-Optical Instrumentation Engineers (SPIE), 2019. pp. 501-508. https://doi.org/10.1117/12.2522668
Pobar, Miran; Ivašić-Kos, Marina

Cite this document

Pobar, M. & Ivašić Kos, M. (2019). Detection of the leading player in handball scenes using Mask R-CNN and STIPS. In A. Verikas, (Ed.), D. Nikolaev, (Ed.), P. Radeva, (Ed.), J. Zhou, (Ed.), Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018) (pp. 501-508). Society of Photo-Optical Instrumentation Engineers (SPIE). doi: 10.1117/12.2522668

Pobar, Miran and Marina Ivašić Kos. "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), edited by A. Verikas, edited by D.P. Nikolaev, edited by P. Radeva, edited by J. Zhou, Society of Photo-Optical Instrumentation Engineers (SPIE), 2019, pp. 501-508. https://urn.nsk.hr/urn:nbn:hr:195:714143

Pobar, Miran and Marina Ivašić Kos. "Detection of the leading player in handball scenes using Mask R-CNN and STIPS." In Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 501-508. Society of Photo-Optical Instrumentation Engineers (SPIE), 2019. Accessed 2024 May 06. https://urn.nsk.hr/urn:nbn:hr:195:714143

Pobar, M. and Ivašić Kos, M. (2019) 'Detection of the leading player in handball scenes using Mask R-CNN and STIPS', in Verikas, A. (ed.), Nikolaev, D. (ed.), Radeva, P. (ed.), Zhou, J. (ed.), Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), Society of Photo-Optical Instrumentation Engineers (SPIE), pp. 501-508. Available at: https://urn.nsk.hr/urn:nbn:hr:195:714143 (Accessed 06 May 2024)

Pobar M, Ivašić Kos M. Detection of the leading player in handball scenes using Mask R-CNN and STIPS. In: A. Verikas, ed., D. Nikolaev, ed., P. Radeva, ed., J. Zhou, ed. Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018). Society of Photo-Optical Instrumentation Engineers (SPIE); 2019. Pp. 501-508. [cited 2024 May 06] Available at: https://urn.nsk.hr/urn:nbn:hr:195:714143

M. Pobar and M. Ivašić Kos, "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), A. Verikas et al., Eds. Society of Photo-Optical Instrumentation Engineers (SPIE), 2019. [Online] Available at: https://urn.nsk.hr/urn:nbn:hr:195:714143 [Accessed: 06 May 2024]

Please login to the repository to save this object to your list.
Metadata
Title (english)Detection of the leading player in handball scenes using Mask R-CNN and STIPS
AuthorMiran Pobar https://orcid.org/0000-0001-5604-2128
AuthorMarina Ivašić-Kos https://orcid.org/0000-0002-1940-5089
EditorA. Verikas
EditorD.P. Nikolaev
EditorP. Radeva
EditorJ. Zhou
Author's institutionUniversity of Rijeka
(Faculty of Informatics and Digital Technologies)
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Information and Communication Sciences
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Artificial Intelligence
Abstract (english)
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.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionAccepted version
Publication titleProc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018)
Numberingvol. 11041, pp. 501-508
ISBN978-151062748-2
DOIhttps://doi.org/10.1117/12.2522668
URN:NBNurn:nbn:hr:195:714143
Publication2019
ProjectNumber: IP-2016-06-8345
Title (croatian): Automatsko raspoznavanje akcija i aktivnosti u multimedijalnom sadržaju iz domene sporta
Title (english): Automatic recognition of actions and activities in multimedia content from sports domain
Acronym: RAASS
Leader: Marina Ivašić Kos
Jurisdiction: Croatia
Funding stream: IP
ConferenceTitle: 11th International Conference on Machine Vision, ICMV 2018
Acronym: ICMV 2018
Location: Muenchen, Germany
Start date: 2018-11-01
End date: 2018-11-03
Assembly type: Lecture
Document URLhttps://www.spiedigitallibrary.org/conference-proceedings-of-spie/11041/110411V/Detection-of-the-leading-player-in-handball-scenes-using-Mask/10.1117/12.2522668.fullfull?SSO=1
Type of resourceText
PublisherSociety of Photo-Optical Instrumentation Engineers (SPIE)
Access conditionsOpen access
Terms of useLicence In copyright icon
Public noteCopyright 2019 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.
Created on2023-02-12 20:02:57