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Enhancing Augmented Reality with Uncertain Transformations in Scene Graphs

Explore the incorporation of uncertain transformations in a scene graph to improve Augmented Reality (AR) experiences. Discover the significance of registration errors, components, limitations, and ongoing advancements in AR technology. Learn about osgAR architecture, error estimation techniques, and the utilization of multiple trackers in AR systems.

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Enhancing Augmented Reality with Uncertain Transformations in Scene Graphs

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  1. osgAR: a Scene Graph with Uncertain Transformations Enylton Machado CoelhoBlair MacIntyre Augmented Environments Lab, GVU - CoC Simon Julier Naval Research Lab

  2. Topics • What is AR? • Registration Error • Scene graphs & osgAR • Components • Limitations • Current & future work

  3. Augmented Reality • Augment, not replace, the physical world with computer-generated objects

  4. AR in Maintenance • Microvision Honda trial • Access to maintenance library Reference www.microvision.com/hondatrial

  5. AR Using Visually Coupled Head-worn Displays • Combine graphics with physical world

  6. Registration Error • Misalignment between the computer generated graphics and the physical object

  7. Registration Error • Commonly used approach • Better trackers • More accurate modeling and calibration • Faster computers • Not practical in real situations • Trackers may break • Knowledge will never be complete

  8. Registration Error • Our approach • Assume errors will always exist • Estimate resulting registration errors • Use error estimates to drive the graphics • Developers concentrate on the intent of the augmentations • Decouple from tracker characteristics

  9. Registration Error • Changing what is being displayed ameliorates the registration error LABELS

  10. Registration Error • Once the registration error can be estimated, different augmentation techniques can be tested • Estimating the error at run time is the hard part Reference www.microvision.com/hondatrial

  11. Topics • What is AR? • Registration Error • Scene graphs & osgAR • Components • Limitations • Current & future work

  12. Scene Graphs • Rigid transformations • Hierarchical representation • Widely adopted • Inventor, Java3D,…

  13. Scene Graphs with Uncertainty • Error estimates are propagated down the graph

  14. Previous Work:Statistical Error Estimation • Individual vertices • 2D screen region Reference VR’02 –Estimating and Adapting to Registration Errors in AR Systems

  15. osgAR:Architecture • Based on OpenSceneGraph (www.openscenegraph.org) • Extended to Augmented Reality • Support for AR • Uncertainty Reference ISMAR’04 –osgAR: A Scene Graph with Uncertain Transformations

  16. osgAR:AR Support • Video in the background • Tracker support • VRPN • ARToolkit • 2D interface manager

  17. osgAR:Computing the Estimate • Model the Uncertainty as a Gaussian • Adds a covariance matrix to the original 4x4 matrix transformation

  18. Bounding Regions • Inner: Always inside the object • Outer: Contains the object BOUNDER

  19. osgAR:Exposing the Estimate • Region: polygonal representation of the regions • Assessment: single value corresponding to the object’s registration error

  20. osgAR:Examples of Using the Estimates • Region • Label Placer • Bounder • Assessment • LOE CALLOUTS Reference ISAR’00 –Adapting to Registration Errors Using Level of Error (LOE) Filtering

  21. Multiple Trackers:Transformation Combiner • Multiple paths to a transform • Callback function picks which to use • Parameter: list of error estimates • Return: which path and estimate to use

  22. Multiple Trackers:Transformation Combiner COMBINER Base Sensor Camera COMB+BOUNDER

  23. osgAR:Architecture • AR Support • Estimate • Computation • Expose • Examples • Multiple Trackers

  24. Observations • Should use shortest path in graph • Camera tracker • Hack: reset error at camera • Head/object tracked with same sensor • Solution: more elaborate bookkeeping/traversal • Leverage redundant information

  25. Camera Uncertainty attached to the world attached to the camera

  26. Pending Transforms • Transformations other then tracker transformations are updated by the system PENDING

  27. Current and Future Work • Generic model that computes the optimal registration error estimate • Exploit the redundancy in the system • Possibility of adding interaction • Applicability and limitations of current computer graphics models

  28. Acknowledgements • Members of the AEL and GVU for many discussions and ideas • ONR grant N000140010361 FOR MORE INFO... www.cc.gatech.edu/ael

  29. Error Estimation • Compute statistical properties for each vertex of an object • Aggregate these estimates per object

  30. Statistical Error Estimation(Simon Julier, NRL) • Unscented Transformation • Easy to implement • More accurate than linearization • Fast

  31. Error Estimate Aggregation • 2D Convex Hull • Project error bounds on 2D screen • Compute convex hull

  32. osgAR: Traversals • Optimizer • 3D uncertainty propagation • Registration error computation

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