Sports Video Analysis: From Semantics to Tactics

  • Guangyu Zhu
  • Changsheng Xu
  • Qingming Huang
Part of the Signals and Communication Technology book series (SCT)


Sports content is expected to be a key driver for compelling new infotainment applications and services because of its mass appeal and inherent structures that are amenable for automatic processing. Due to its wide viewership and tremendous commercial value, there has been an explosive growth in the research area of sports video analysis. The existing work on sports video analysis can be classified as two perspectives in terms of semantic analysis and tactic analysis. For semantic analysis, the objective is to detect the semantic events in the sports video and present them to the common users. Most of the current effort of semantic analysis of sports videos is devoted to event detection. Event detection is essential for sports video summarization, indexing, and retrieval, and extensive research efforts have been devoted to this area. However, the previous approaches rely heavily on video content itself and require the whole video content for event detection. Due to the semantic gap between low-level features and high-level events, it is difficult to come up with a generic framework to achieve a high accuracy of event detection. In addition, the dynamic structures from different sports domains further complicate the analysis and impede the implementation of live-event detection systems. In this chapter, we present a novel approach for event detection from the live sports game using Web-casting text and broadcast video. Moreover, we give scenarios to illustrate how to apply the proposed solution to professional and consumer services. In contrast, tactic analysis aims to recognize and discover tactic patterns in the games and present the results to the professionals in the tactic mode. Most of existing approaches on event detection in sports video are general audience oriented, where the extracted events are then presented to the audience without further analysis. However, professionals such as soccer coaches are more interested in the tactics used in the events. Consequently, we present a novel approach to extract tactic information from the goal event in broadcast soccer video and present the goal event in a tactic mode to the coaches and sports professionals.


Support Vector Regression Goal Event Sport Video Soccer Game Soccer Video 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.NEC Laboratories AmericaUSA

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