Open Access iconOpen Access

ARTICLE

crossmark

Research on Tracking and Registration Algorithm Based on Natural Feature Point

by Tingting Yang1,*, Shuwen Jia1, Boxiong Yang1, Chenxi Kan2

1 Shcool of Information and Intelligence Engineering University of Sanya, Sanya, China
2 Engineering Technology and Applied Science, Centennial College, Toronto, Canada

* Corresponding Author: Tingting Yang. Email: email

Intelligent Automation & Soft Computing 2021, 28(3), 683-692. https://doi.org/10.32604/iasc.2021.017235

Abstract

In the augmented reality system, the position and direction of the user’s point of view and line of sight in the real scene is acquired in real-time. The position and direction information will determine the exact position of the virtual object of the real scene. At the same time, various coordinate systems are established according to the user’s line of sight. So registration tracking technology is very important. The paper proposes an accurate, stable, and effective augmented reality registration algorithm. The method adopts the method of ORB (oriented FAST and rotated BRIEF) features matching combined with RANSAC (random sample consensus) to obtain the homography matrix and then uses the KLT (kanade-lucas-tomasi) tracking algorithm to track the mark, which is a better solution. The error accumulation defect based on the natural feature tracking registration method is improved, and the stability and accuracy of the registration are improved. Experiments have proved that the algorithm in this paper is accurate, stable, and effective, and can complete the virtual and real registration tasks accurately and stably even when the marked part is not visible.

Keywords


Cite This Article

APA Style
Yang, T., Jia, S., Yang, B., Kan, C. (2021). Research on tracking and registration algorithm based on natural feature point. Intelligent Automation & Soft Computing, 28(3), 683-692. https://doi.org/10.32604/iasc.2021.017235
Vancouver Style
Yang T, Jia S, Yang B, Kan C. Research on tracking and registration algorithm based on natural feature point. Intell Automat Soft Comput . 2021;28(3):683-692 https://doi.org/10.32604/iasc.2021.017235
IEEE Style
T. Yang, S. Jia, B. Yang, and C. Kan, “Research on Tracking and Registration Algorithm Based on Natural Feature Point,” Intell. Automat. Soft Comput. , vol. 28, no. 3, pp. 683-692, 2021. https://doi.org/10.32604/iasc.2021.017235



cc Copyright © 2021 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 2023

    View

  • 1248

    Download

  • 0

    Like

Share Link