Earticle

초록

영어

In this paper, we propose a novel method to solve the problem of targets association and tracking across multiple cameras of non-overlapping views. The method is divided into two parts. One is an improvement on appearance transfer model, another is an improvement on spatio-temporal transfer model. To learn inter-camera appearance transfer models, lαβ color space is used to calibrate images. By this way, the overall and local information can be used, which has advantage to color transform correction. To learn spatio-temporal transfer model, entry/exit zones of a non-overlapping topology can be effectively estimated by defining valid link and using clustering method. Then a kind of time constrain is set between two nodes to judge whether there is correlation of observations. Experiments show the effectiveness of the proposed method.

목차

Abstract
 1. Introduction
 2. Improved on Appearance Transfer Model
 3. Improved on Spatio-temporal Transfer Model
 4. Experimental Results
 5. Conclusion
 References

키워드

저자

• Liu Suolan [ School of Automation, Southeast University, Nanjing 210096, China, School of Information Science & Engineering, Changzhou University, Changzhou 213164, China, Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX 75080, USA ]
• Wang Jia [ School of Information Science & Engineering, Changzhou University, Changzhou 213164, China ]
• Sun Changyin [ School of Automation, Southeast University, Nanjing 210096, China ] Corresponding Author

참고문헌

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간행물

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• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605