Earticle

초록

영어

A corner event detection method based on HMM (Hidden Markov Model) in soccer videos. Through analysis of the semantic structure of corner events, define and extract six multi- modal semantic clues to describe shot sequences, which constitute observation sequences as the HMM model input. By the iterative training of the HMM model and the continuous optimization of model parameters, construct the HMM model of corner events. From two aspects of audio and video, dig the inherent pattern of corner events and realize corner events automatic detection based on HMM accurately. The experimental results show that the present method achieves 89.6% recall and 96.3% precision, which has the better performance.

목차

Abstract
 1. Introduction
 2. Retrieval of Semantic Clues of Corner Kick Episodes in Football Videos
  2.1. Field Rate (FR)
  2.2. Player Ratio (PR)
  2.3. Midfield Area (MA)
  2.4. Penalty Area (PA)
  2.5. Corner area (CA)
  2.6. Audio Energy
 3. Detection of Corner Kick Episodes in Football Videos based on HMM
  3.1. Markov Chains
  3.2. Training and Reasoning of HMM
 4. Experimental Analysis and Results
  4.1. Experiment on the Retrieval of Semantic Clues
  4.2. Experiment on the Detection of Corner Kick Episodes based on HMM
 5. Conclusion
 References

키워드

저자

• Haitao Yang [ Beijing University of Technology, Beijing 100000, China ]
• Jia Wang [ Beijing University of Technology, Beijing 100000, China ]
• Jingmeng Sun [ Physical Education Department, Harbin Engineering University, Harbin 150000, China ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605