Earticle

초록

영어

In this paper, we propose a novel visual saliency detection method using motion segmentation. We group the corner point trajectories using a two stage clustering algorithm. The most stable trajectories are pre-clustered using mean shift in the first stage. Then, we propose an unsupervised clustering method to cluster the trajectories and detect the number of motions automatic. At last, the motion saliency map is generated with the segmented spare feature points. Experimental results show that our proposed method is capable of achieving both good accurate and the stable performance.

목차

Abstract
 1. Introduction
 2. Motion Segmentation Based on Trajectory Clustering
  2.1. Trajectory Feature Extraction
  2.2. The Preprocessing Based on Mean Shift
  2.3. Unsupervised Clustering Algorithm of Motion Vector
 3. Generation of Saliency Map
 4. Experimental Results
 5. Conclusion
 References

키워드

저자

• Man Hua [ School of Computer Science, Civil Aviation Flight University of China, GuangHan, Sichuan, 618307, China ]
• Yanling Li [ School of Computer Science, Civil Aviation Flight University of China, GuangHan, Sichuan, 618307, 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