Circular data matrix fiducial system and robust image processing for a wearable vision-inertial self-tracker

A wearable low-power hybrid vision-inertial tracker has been demonstrated based on a flexible sensor fusion core architecture, which allows easy reconfiguration by plugging-in different kinds of sensors. A particular prototype implementation consists of one inertial measurement unit and one out-ward-looking wide-angle smart camera, with a built-in DSP to run all required image-processing tasks. The smart camera operates on newly designed 2D bar-coded fiducials printed on a standard black-and-white printer. The fiducial design allows having thousands of different codes, thus enabling uninterrupted tracking throughout a large building or even a campus at very reasonable cost. The system operates in various real-world lighting conditions without user intervention due to homomorphic image processing algorithms for extracting fiducials in the presence of very non-uniform lighting.

[1]  Ronald Azuma,et al.  A motion-stabilized outdoor augmented reality system , 1999, Proceedings IEEE Virtual Reality (Cat. No. 99CB36316).

[2]  M. F.,et al.  Bibliography , 1985, Experimental Gerontology.

[3]  Khoi Nguyen,et al.  Computer-vision-based registration techniques for augmented reality , 1996, Other Conferences.

[4]  Zhengyou Zhang,et al.  Flexible camera calibration by viewing a plane from unknown orientations , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[5]  Ulrich Neumann,et al.  A Multi-ring Color Fiducial System and A Rule-Based Detection Method for Scalable Fiducial-tracking Augmented Reality , 1998 .

[6]  Gregory F. Welch.  Hybrid Self-Tracker: An Inertial/Optical Hybrid Three-Dimensional Tracking System , 1995 .

[7]  Suya You,et al.  Fusion of vision and gyro tracking for robust augmented reality registration , 2001, Proceedings IEEE Virtual Reality 2001.

[8]  Lance B. Gatrell,et al.  Accuracy of locating circular features using machine vision , 1992, Other Conferences.

[9]  Mark A. Livingston,et al.  Superior augmented reality registration by integrating landmark tracking and magnetic tracking , 1996, SIGGRAPH.

[10]  G. Klinker,et al.  A fast and robust line-based optical tracker for augmented reality applications , 1999 .

[11]  Naokazu Yokoya,et al.  A stereo vision-based augmented reality system with an inertial sensor , 2000, Proceedings IEEE and ACM International Symposium on Augmented Reality (ISAR 2000).

[12]  Lance B. Gatrell,et al.  Robust image features: concentric contrasting circles and their image extraction , 1992, Other Conferences.

[13]  Nassir Navab,et al.  E-commerce direct marketing using augmented reality , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[14]  Ulrich Neumann,et al.  A self-tracking augmented reality system , 1996, VRST.

[15]  Jorge Herbert de Lira,et al.  Two-Dimensional Signal and Image Processing , 1989 .

[16]  Eric Foxlin,et al.  Generalized architecture for simultaneous localization, auto-calibration, and map-building , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[17]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Hirokazu Kato,et al.  Collaborative Mixed Reality , 1999 .

[19]  Eric Foxlin,et al.  VIS-Tracker: a wearable vision-inertial self-tracker , 2003, IEEE Virtual Reality, 2003. Proceedings..