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Tracking multiple players in beach volleyball videos

  • Xiaokang Jiang
  • , Zheng Liu
  • , Yunhong Wang*
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Multi-object tracking has been a difficult problem in recent years, especially in complex scenes such as player tracking in sports videos. Player movements are often complex and abrupt. In this paper, we focus on the problem of tracking multiple players in beach volleyball videos. To handle the difficulties of player tracking, we follow the popular tracking-by-detection framework in multi-object tracking and adopt the multiple hypotheses tracking (MHT) algorithm to solve the data association problem. To improve the efficiency of the MHT, we use motion information from Kalman filter and train an online appearance model of each track hypothesis. An auxiliary particle filter method is adopted to handle the missing detection problem. Furthermore, we obtain the significant performance on our beach volleyball datasets, which demonstrate the effectiveness and efficiency of the proposed method.

Original languageEnglish
Title of host publicationIntelligent Visual Surveillance - 4th Chinese Conference, IVS 2016, Proceedings
EditorsZhang Zhang, Kaiqi Huang
PublisherSpringer Verlag
Pages65-71
Number of pages7
ISBN (Print)9789811034756
DOIs
StatePublished - 2016
Event4th Chinese Conference on Intelligent Visual Surveillance, IVS 2016 - Beijing, China
Duration: 19 Oct 201619 Oct 2016

Publication series

NameCommunications in Computer and Information Science
Volume664 CCIS
ISSN (Print)1865-0929

Conference

Conference4th Chinese Conference on Intelligent Visual Surveillance, IVS 2016
Country/TerritoryChina
CityBeijing
Period19/10/1619/10/16

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