An improved augmented reality system based on AndAR

• We present an adaptive Augmented Reality (AR) architecture.
• The improved AndAR can augment reality based on natural features.
• The solution can augment the reality anywhere.
• The presented approach improves system speed and extends tracking range.

AndAR is a project applied to develop Mobile Augmented Reality (MAR) applications on the android platform. The existing registration technologies of AndAR are still base on markers assume that all frames from all videos contain the target objects. With the need of practical application, the registration based on natural features is more popular, but the major limitation of the registration is that many of them are based on low-level visual features. This paper improves AndAR by introducing the planar natural features. The key of registration based on planar natural features is to get the homography matrix which can be calculated with more than 4 pairs of matching feature points, so a 3D registration method based on ORB and optical flow is proposed in this paper. ORB is used for feature point matching and RANSAC is used to choose good matches, called inliers, from all the matches. When the ratio of inliers is more than 50% in some video frame, inliers tracking based on optical flow is used to calculate the homography matrix in the latter frames and when the number of inliers successfully tracked is less than 4, then it goes back to ORB feature point matching again. The result shows that the improved AndAR can augment not only reality based on markers but also reality based on planar natural features in near real time and the hybrid approach can not only improve speed but also extend the usable tracking range.