Signal, Image and Video Processing

, Volume 11, Issue 1, pp 171–178 | Cite as

Automatic analysis of broadcast football videos using contextual priors

  • Rahul Anand Sharma
  • Vineet Gandhi
  • Visesh Chari
  • C. V. Jawahar
Original Paper
First Online:
Received:
Revised:
Accepted:

Abstract

The presence of standard video editing practices in broadcast sports videos, like football, effectively means that such videos have stronger contextual priors than most generic videos. In this paper, we show that such information can be harnessed for automatic analysis of sports videos. Specifically, given an input video, we output per-frame information about camera angles and the events (goal, foul, etc.). Our main insight is that in the presence of temporal context (camera angles) for a video, the problem of event tagging (fouls, corners, goals, etc.) can be cast as per frame multi-class classification problem. We show that even with simple classifiers like linear SVM, we get significant improvement in the event tagging task when contextual information is included. We present extensive results for 10 matches from the recently concluded Football World Cup, to demonstrate the effectiveness of our approach.

Keywords

Sports video analysis Broadcast video Event classification Content-based retrieval 
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Supplementary material

11760_2016_916_MOESM1_ESM.mp4 (2.4 mb)
Supplementary material 1 (mp4 2413 KB)
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Supplementary material 2 (mp4 4383 KB)
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Supplementary material 3 (mp4 5320 KB)
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Supplementary material 4 (mp4 12446 KB)
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Supplementary material 5 (mp4 3487 KB)

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Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  • Rahul Anand Sharma
    • 1
  • Vineet Gandhi
    • 1
  • Visesh Chari
    • 1
  • C. V. Jawahar
    • 1
  1. 1.Center for Visual Information TechnologyInternational Institute of Information TechnologyGachibowli, HyderabadIndia

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