2D Histogram-based player localization in broadcast volleyball videos

Chun Chieh Hsu, Hua-Tsung Chen, Chien Li Chou, Suh-Yin Lee

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Player location is one of the most informative cues for obtaining tactics arrangement and collecting descriptive game statistics. However, state-of-the-art supervised learning-based methods for player localization require a large amount of labeled training data. Hence, the development of automatic systems for player localization becomes indispensable. Volleyball games reach a huge audience base and contain a variety of tactical strategies, necessitating the implementation of systems for inferring tactics and analyzing formations automatically. Therefore, a novel 2D histogram-based player localization method capable of locating players with occlusions is developed and presented in this paper. The proposed system is able to automatically detect the court lines for camera calibration, extract players by calculating both x and y histograms of extracted player masks, and visualize the team formations on real-world court model. The experiments on broadcast volleyball videos demonstrate efficient and effective results against a traditional object segmentation method (connected component analysis) and a supervised learning approach utilizing histogram of oriented gradient features.
Original languageEnglish
Pages (from-to)325-341
Number of pages7
JournalMultimedia Systems
Issue number3
StatePublished - Jun 2016


  • Sports video analysis; People localization; Camera calibration; Multimedia system; Pattern recognition; Broadcast volleyball video

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