Interpreting sports tactic based on latent context-free grammar

Xingzhong Xu, Hong Man

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

2 Scopus citations

Abstract

In this paper, latent context-free grammar (LCFG) is proposed to probabilistically interpret high level tactic concepts in sports video. From domain knowledge, a sports concept typically consists of multiple levels of recursive or non-recursive sub-concepts. Conventional shallow models, e.g. HMMs, have difficulties in characterizing such complex semantics. On the other hand, a comprehensive Bayesian network may require detailed design and parameterization, which is frequently impractical. LCFG is introduced as an extension to stochastic context-free grammar (SCFG), which jointly uses a set of low level discriminative terminals from video analysis and a set of intermediate context-free rules from sports domain knowledge to model the complex athletes' behaviors and the underlying tactics. The classical 'pick-and-roll' tactic in basketball game is studied in our experimental work. The experimental results demonstrated the rich representation and interpretation powers of LCFG through its probabilistic parsing trees.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
Pages4072-4076
Number of pages5
ISBN (Electronic)9781479983391
DOIs
StatePublished - 9 Dec 2015
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: 27 Sep 201530 Sep 2015

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2015-December
ISSN (Print)1522-4880

Conference

ConferenceIEEE International Conference on Image Processing, ICIP 2015
Country/TerritoryCanada
CityQuebec City
Period27/09/1530/09/15

Keywords

  • semantic parsing
  • sports video analysis
  • stochastic context-free Grammar

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