Earticle

초록

영어

In recent, object recognition and tracking systems have been developed that use local invariant features from Shift Invariant Feature Transform algorithm. Most of them are implemented by distance matching of descriptor features between the reference and the next consecutive frame image. Among the matched keypoints generated from SIFT descriptor matching, there are some mismatched keypoints when keypoint location information is considered. These location-mismatched keypoints could be affected to object tracking perfomance. To achieve a stable tracking it is necessary that these are detected and discarded in tracking action. In this paper a robust object tracking system is presented that strengthen stability in tracking by eleminating location-mismatched keypoints. Experimental results show that a stable and robust tracking can be achieved in a test video sequence includes multiple objects.

목차

Abstract
 1. Introduction
 2. Scale Invariant Feature Transform
 3. The Proposed Algorithm
 4. Object Detection and Location Matching
  4.1 Object Detection
  4.2 Keypoint Extraction
  4.3 Keypoint Matching
  4.4 Selection of Location-matched Keypoints
 5. Experimental Results of Object Tracking
 6. Conclusion
 References

키워드

저자

• Seok-Wun Ha [ Dept. of Informatics , Engineering Research Institute, Gyeongsang National University, 900 Gazwa-Dong, Jinju, Gyeongnam, Rep. of Korea ]
• Yong-Ho Moon [ Dept. of Informatics , Engineering Research Institute, Gyeongsang National University, 900 Gazwa-Dong, Jinju, Gyeongnam, Rep. of Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605