A Stable and Accurate Marker-less Augmented Reality Registration Method.

Gao, Q.H., Wan, T.R., Tang, W. and Chen, L., 2017. A Stable and Accurate Marker-less Augmented Reality Registration Method. In: Cyberworlds 2017, 20-22 September 2017, University of Chester, UK.

Full text available as:

[img]
Preview
PDF
CW_2017_paper_63.pdf - Accepted Version

1MB

Official URL: http://cw2017.org/

Abstract

Markerless Augmented Reality (AR) registration using the standard Homography matrix is unstable, and for image-based registration it has very low accuracy. In this paper,we present a new method to improve the stability and the accuracy of marker-less registration in AR. Based on the VisualSimultaneous Localization and Mapping (V-SLAM) framework,our method adds a three-dimensional dense cloud processingstep to the state-of-the-art ORB-SLAM in order to deal withmainly the point cloud fusion and the object recognition. Ouralgorithm for the object recognition process acts as a stabilizer toimprove the registration accuracy during the model to the scenetransformation process. This has been achieved by integrating theHough voting algorithm with the Iterative Closest Points(ICP)method. Our proposed AR framework also further increasesthe registration accuracy with the use of integrated cameraposes on the registration of virtual objects. Our experiments show that the proposed method not only accelerates the speed of camera tracking with a standard SLAM system, but also effectively identifies objects and improves the stability of marker-less augmented reality applications.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Augmented Reality ; SLAM Algorithm
Group:Faculty of Science & Technology
ID Code:29499
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:24 Jul 2017 13:49
Last Modified:25 Sep 2017 08:57

Downloads

Downloads per month over past year

More statistics for this item...
Repository Staff Only -