Earticle

초록

영어

Aiming at solving problem of points’ redundancy caused by full automatically detecting points and the problem of large workload caused by picking all points manually, I advanced a new method of picking points which is based on Human-Computer Interaction in our 3D reconstruction platform after automatically detecting points. We first detected and matched points automatically and got the homograph matrix between two images, then projected points which were picked by hand on the one image to the other image, at last we would search the interesting feature points in the neighborhood of corresponding points in the two images. Experiments have shown that this method decreases the redundancy brought by large number of points and successfully finds the important feature points, so it lays a good foundation for 3D reconstruction.

목차

Abstract
 1. Introduction
 2. The Whole Progress of Algorithm
 3. Feature Point Detecting and Matching Algorithm
  3.1. Feature Point Detector
  3.2. Feature Point Descriptor
  3.3. Feature Point Matching
 4. Transformation Matrix Acquisition Algorithm
 5. Feature Points Searching in Small Region Algorithm
 6. Experiment and Conclusion
 Acknowledgements
 Reference

키워드

저자

• Zhu Shi Wei [ Southeast University Southeast UniversitySoutheast University ]
• Zhang Xiao Guo [ Southeast University Southeast UniversitySoutheast University ]
• Lv Jia Dong [ Southeast University Southeast UniversitySoutheast University ]
• Wang Qing [ Southeast University ]

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