Markerless Pose Tracking for Augmented Reality

In this paper a new approach is presented for markerless pose tracking in augmented reality. Using a tracking by detection approach, we estimate the 3D camera pose by detecting natural feature points in each input frame and building correspondences between 2D feature points. Instead of modeling the 3D environment, which is changing constantly and dynamically, we use a virtual square to define a 3D reference coordinate system. Camera pose can hence be estimated relative to it and the calculated 3D pose parameters can be used to render virtual objects into the real world. We propose and implement several strategies for robust matching, pose estimation and refinement. Experimental evaluation has shown that the approach is capable of online pose tracking and augmentation.