Markerless augmented reality system based on planar object tracking

Typically, vision-based AR systems operate on the basis of prior knowledge of the environment such as a square marker. One problem of traditional marker-based AR system has a limitation that the marker has to be located in the sensing range. Therefore, there have been considerable research efforts for the techniques known as real-time camera tracking, in which the system attempts to add unknown 3D features to its feature map, and these then provide registration even when the reference map is out of the sensing range. In this paper, we describe a real-time camera tracking framework specifically designed to track a monocular camera in a desktop workspace. Basic idea of the proposed scheme is that a real-time camera tracking is achieved on the basis of a plane tracking algorithm. Also we suggest a method for re-detecting features to maintain registration of virtual objects. The proposed method can cope with the problem that the features cannot be tracked, when they go out of the sensing range. It can be applicable to an augmented reality system for mobile computing environment.

[1]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[2]  Neil A. Thacker,et al.  Tutorial: Computing 2D and 3D Optical Flow. , 2004 .

[3]  Dieter Schmalstieg,et al.  Robust and unobtrusive marker tracking on mobile phones , 2008, 2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality.

[4]  Ronald Azuma,et al.  Recent Advances in Augmented Reality , 2001, IEEE Computer Graphics and Applications.

[5]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[6]  Tobias Höllerer,et al.  Multithreaded Hybrid Feature Tracking for Markerless Augmented Reality , 2009, IEEE Transactions on Visualization and Computer Graphics.

[7]  Sangkeun Lee,et al.  Real-time camera tracking using a particle filter and multiple feature trackers , 2009, 2009 International IEEE Consumer Electronics Society's Games Innovations Conference.

[8]  Olivier Stasse,et al.  MonoSLAM: Real-Time Single Camera SLAM , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Guangjun Zhang,et al.  A New Sub-Pixel Detector for X-Corners in Camera Calibration Targets , 2005, WSCG.

[10]  G. Klein,et al.  Parallel Tracking and Mapping for Small AR Workspaces , 2007, 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality.

[11]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .