Earticle

초록

영어

In this paper we discuss about a target tracking algorithm based on Mean Shift and Kalman Filter, which is suitable for high speed moving target tracking. The basic Mean Shift algorithm is described in this paper as well. Although basic Mean Shift algorithm can realize target tracking without arguments or searching all the areas effectively, it has shortcomings which can limit its effectiveness under some conditions such as the target covered by something when moving or the target moving with high speed. In order to make Mean Shift target tracking algorithm satisfies the practical application, such as high speed moving target tracking, we analysis the lack of basic Mean Shift algorithm, then we design a target tracking algorithm which combine an improved Mean Shift target tracking algorithm with Kalman Filter(IMKTT). In the fourth section of the paper, we apply the algorithm to a monitoring system of Shanghai University. The result shows that the algorithm designed in this paper can effectively track high speed moving target, such as a car.

목차

Abstract
 1. Introduction
 2. Improved Mean Shift
  2.1. Mean Shift
  2.2. Improved Mean Shift
  2.3 Improved Mean Shift Target Tracking Algorithm
 3. Target Tracking Algorithm based on Improved Mean Shift and Kalman Filter
  3.1. Deficiencies of Mean Shift
  3.2. Kalman Filter
  3.3. IMKTT-Target Tracking Algorithm based on Improved Mean Shift and Kalman Filter
 4. Application of IMKTT
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Bian Minjie [ School of Computer Engineering and Science Shanghai University, 200444 Shanghai, P.R. China ]
• Honghao Gao [ Computing Center, Shanghai University, 200444 Shanghai, P.R. China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605