Earticle

초록

영어

The paper presents a method which bases on support vector machine(SVM) and particle filtering for detecting and tracking player in the broadcast sports video. Firstly, through the combination of Support Vector Classification and CourtSegmentationmethod, it proposes the algorithm for examining automatically members in those videos, which is used to initialize the trace of subsequent visual objects; secondly, by combing support vector regression frame and the one of sequential Monte Carlo, it brings forth the improved particle filtering algorithm which is applied to follow visual objects, enabling the traditional particle filtering method to achieve robust trail of such targets even when the particle set is small, together with effective enhancement of the running efficiency of tracking system.

목차

Abstract
 1. Introduction
 2. Player Detection based on Court Segmentation
 3. Player Track Based on SVR and Particle Filtering
  3.1. Introduction of Particle Filtering
  3.2. Problems with Traditional Particle Filtering Method
  3.3 Improved Particle Filtering Algorithm based on Support Vector Regression
 4. Moving Object Detection and Tracking Framework Based on SVM and Particle Filtering
 5. Experiment Design and Results
  5.1 Testing Results of Player Inspection
  5.2. Comparison Results Support Vector Regression Particle Filter with the Traditional Particle Filter
  5.3. Experimental Results of Tracking Player
 6. Conclusion
 References

키워드

저자

• Yang Wang [ Physical Education Department, Harbin Engineering University, Harbin 150000, China ]
• Yueqiu Han [ College of International Cooperation Education, Harbin Engineering University, Harbin 150000, China ]
• Deming Zhang [ Heilongjiang University of Chinese Medicine,Harbin 150000, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605