Hybrid Tracking for Augmented Reality

Accurate registration between real and virtual objects is critical for Augmented Reality (AR) applications. State of the art shows that no tracking device is individually adequate. We present a data fusion framework that combines orientation measurements of different tracker devices. It has been designed to work with a video–based tracker subsystem and an inertial tracker. Thanks to its flexibility the system can use orientation measurements produced by any kind and number of trackers, no matter their rate or physical configuration. The core of this fusion system is a Kalman filter with only one process and measurement model shared by all the trackers. The system weights each tracker according to the quality of their measurements. We have tested the system with synthetic and real orientation data to evaluate its fusion capabilities and find its limitations. This analysis leads our future work to the development of a drift corrector and to extend the filter to make it dynamically adaptive.

[1]  Axel Pinz,et al.  The integration of optical and magnetic tracking for multi-user augmented reality , 1999, Comput. Graph..

[2]  Olivier D. Faugeras,et al.  What can be seen in three dimensions with an uncalibrated stereo rig , 1992, ECCV.

[3]  Mongi A. Abidi,et al.  Pose and motion estimation from vision using dual quaternion-based extended kalman filtering , 1997 .

[4]  Touradj Ebrahimi,et al.  Tracking and User Interface for Mixed Reality , 2005 .

[5]  Eric Foxlin,et al.  Inertial head-tracker sensor fusion by a complementary separate-bias Kalman filter , 1996, Proceedings of the IEEE 1996 Virtual Reality Annual International Symposium.

[6]  Jannick P. Rolland,et al.  A Survey of Tracking Technologies for Virtual Environments , 2001 .

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

[8]  Dieter Schmalstieg,et al.  Mobile collaborative augmented reality , 2001, Proceedings IEEE and ACM International Symposium on Augmented Reality.

[9]  Axel Pinz.  Consistent Visual Information Processing Applied to Object Recognition Landmark Definition and Real-Time Tracking , 2001, VMV.

[10]  Ronald Azuma,et al.  Hybrid inertial and vision tracking for augmented reality registration , 1999, Proceedings IEEE Virtual Reality (Cat. No. 99CB36316).

[11]  Axel Pinz,et al.  Building a hybrid tracking system: integration of optical and magnetic tracking , 1999, Proceedings 2nd IEEE and ACM International Workshop on Augmented Reality (IWAR'99).

[12]  Tsuneo Yoshikawa,et al.  Accurate image overlay on video see-through HMDs using vision and accelerometers , 2000, Proceedings IEEE Virtual Reality 2000 (Cat. No.00CB37048).

[13]  Reinhold Behringer,et al.  Registration for outdoor augmented reality applications using computer vision techniques and hybrid sensors , 1999, Proceedings IEEE Virtual Reality (Cat. No. 99CB36316).

[14]  A. Pinz,et al.  Inertial tracking for mobile augmented reality , 2002, IMTC/2002. Proceedings of the 19th IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.00CH37276).

[15]  Axel Pinz,et al.  A new optical tracking system for virtual and augmented reality applications , 2001, IMTC 2001. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference. Rediscovering Measurement in the Age of Informatics (Cat. No.01CH 37188).

[16]  Axel Pinz,et al.  A new Combination of Vision-Based and Inertial Tracking for Fully Mobile, Wearable, and Real-Time Operation , 2002 .

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

[18]  Ronald Azuma,et al.  Tracking in unprepared environments for augmented reality systems , 1999, Comput. Graph..

[19]  Emil M. Petriu,et al.  3-D head pose recovery for interactive virtual reality avatars , 2002, IEEE Trans. Instrum. Meas..

[20]  Janne Heikkilä,et al.  Geometric Camera Calibration Using Circular Control Points , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[21]  Ronald Azuma,et al.  Improving static and dynamic registration in an optical see-through HMD , 1994, SIGGRAPH.

[22]  Ronald Azuma,et al.  Tracking requirements for augmented reality , 1993, CACM.

[23]  Long Quan,et al.  Linear N-Point Camera Pose Determination , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[24]  Susumu Tachi,et al.  Multisensor Integrated Prediction for Virtual Reality , 1998, Presence.

[25]  Patrick Bouthemy,et al.  A 2D-3D model-based approach to real-time visual tracking , 2001, Image Vis. Comput..