NOVEL FRAMEWORK FOR SPORTS VIDEO ANALYSIS: A BASKETBALL CASE STUDY

Chun-Min Chen, Ling-Hwei Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

Semantic event and slow motion replay extraction for sports videos have become hot research topics. Most researches analyze every video frame; however, semantic events only appear in frames with scoreboard, whereas replays only appear in frames without scoreboard. Extracting events and replays from unrelated frames causes defects and leads to degradation of performance. In this paper, a novel framework is proposed to tackle challenges of basketball video analysis. In the framework, a scoreboard detector is first provided to divide video frames to two classes, with/without scoreboard. Then, a semantic event extractor is presented to extract semantic events from frames with scoreboard and a slow motion replay extractor is proposed to extract replays from frames without scoreboard. Experimental results show that the proposed framework is practicable for basketball videos. It is expected that the proposed framework can be extended to other sports.
Original languageEnglish
Title of host publication2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP)
PublisherIEEE
Pages961-965
Number of pages5
ISBN (Print)978-1-4799-5751-4
DOIs
StatePublished - 2014
EventIEEE International Conference on Image Processing (ICIP) - Paris, France
Duration: 27 Oct 201430 Oct 2014

Publication series

NameIEEE International Conference on Image Processing ICIP
PublisherIEEE
ISSN (Print)1522-4880

Conference

ConferenceIEEE International Conference on Image Processing (ICIP)
CountryFrance
CityParis
Period27/10/1430/10/14

Keywords

  • Basketball; broadcast video; semantic event extraction; slow motion replay detection; sports video analysis

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  • Cite this

    Chen, C-M., & Chen, L-H. (2014). NOVEL FRAMEWORK FOR SPORTS VIDEO ANALYSIS: A BASKETBALL CASE STUDY. In 2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) (pp. 961-965). (IEEE International Conference on Image Processing ICIP). IEEE. https://doi.org/10.1109/ICIP.2014.7025193