An Improved Augmented Reality Registration Method Based on Visual SLAM.

Authors: Gao, Q.H., Wan, T.R., Tang, W., Chen, L. and Zhang, K.B.

http://eprints.bournemouth.ac.uk/29342/

Start date: 26 June 2017

Journal: Springer Lecture Notes in Computer Science (LNCS) series

Markerless Augmented Reality registration using standard Homography matrix is unstable and has low registration accuracy. In this paper, we present a new method to improve the augmented reality registration method based on the Visual Simultaneous Localization and Mapping (VSLAM). We improved the method implemented in ORB- SLAM in order to increase stability and accuracy of AR registration.

VSLAM algorithm generate 3D scene maps in dynamic camera tracking process. Hence, for AR based on VSLAM utilizes the 3D map of the scene reconstruction to compute the location for virtual object augmen- tation. In this paper, a Maximum Consistency with Minimum Distance and Robust Z-score (MCMD Z) algorithm is used to perform the planar detection of 3D maps, then the Singular Value Decomposition (SVD) and Lie group are used to calculate the rotation matrix that helps to solve the problem of virtual object orientation. Finally, the method integrates camera poses on the virtual object registration. We show experimental results to demonstrate the robustness and registration accuracy of the method for augmented reality applications.

This data was imported from DBLP:

Authors: Gao, Q.H., Wan, T.R., Tang, W., Chen, L. and Zhang, K.B.

Editors: Tian, F., Gatzidis, C., Rhalibi, A.E. and Charles, F.

http://eprints.bournemouth.ac.uk/29342/

https://doi.org/10.1007/978-3-319-65849-0

Journal: Edutainment

Volume: 10345

Pages: 11-19

Publisher: Springer

ISBN: 978-3-319-65848-3

This data was imported from Scopus:

Authors: Gao, Q.H., Wan, T.R., Tang, W., Chen, L. and Zhang, K.B.

http://eprints.bournemouth.ac.uk/29342/

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 10345 LNCS

Pages: 11-19

eISSN: 1611-3349

ISBN: 9783319658483

ISSN: 0302-9743

DOI: 10.1007/978-3-319-65849-0_2

© 2017, Springer International Publishing AG. Markerless Augmented Reality registration using standard Homography matrix is instable and has low registration accuracy. In this paper, we present a new method to improve the augmented reality registration method based on the Visual Simultaneous Localization and Mapping (VSLAM). We improved the method implemented in ORBSLAM in order to increase stability and accuracy of AR registration. VSLAM algorithm generate 3D scene maps in dynamic camera tracking process. Hence, for AR based on VSLAM utilizes the 3D map of the scene reconstruction to compute the location for virtual object augmentation. In this paper, a Maximum Consistency with Minimum Distance and Robust Z-score (MCMD_Z) algorithm is used to perform the planar detection of 3D maps, then the Singular Value Decomposition (SVD) and Lie group are used to calculate the rotation matrix that helps to solve the problem of virtual object orientation. Finally, the method integrates camera poses on the virtual object registration. We show experimental results to demonstrate the robustness and registration accuracy of the method for augmented reality applications.

The data on this page was last updated at 04:50 on February 22, 2019.