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A Framework for Perceptual Studies in Photorealistic Augmented Reality

This research presents a framework for studying photorealistic rendering techniques in augmented reality, focusing on perceptual challenges. The framework includes interactive tasks, global illumination, and differential instant radiosity for real-time rendering. A pilot study evaluated the framework with tasks like distance estimation and object manipulation. Future work includes enhancing the framework with stereo rendering and new studies. The conclusion highlights the potential for new experiments and the impact of different rendering modes on user perception.

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A Framework for Perceptual Studies in Photorealistic Augmented Reality

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  1. A Framework for Perceptual Studies in Photorealistic Augmented Reality Martin Knecht1, Andreas Dünser2,Christoph Traxler1, Michael Wimmer1 and Raphael Grasset3 1 Institute of Computer Graphicsand Algorithms Vienna University of Technology 2 HIT Lab NZ University of Canterbury 3 HIT Lab NZ / ICG University of Canterbury /Graz University of Technology

  2. Introduction • Motivation • Perceptual Issues • Framework • Pilot Study • Limitations • Future Work • Conclusion Martin Knecht

  3. Motivation • Is this a photograph or computer generated? • What visual factors affect your decision? Rademacher P., et al. (2001) Courtesy of Rademacher et al. (2001) Martin Knecht

  4. Motivation • People are very good in judging if an image looks photo-realistic or notBut process behind it not fully understood! • In augmented reality (AR) virtual objects should be rendered in a photorealistic way • Goal: A framework that allows us to study photorealistic rendering techniques at real-time frame rates Martin Knecht

  5. Perceptual Issues • Kruijff E., et al. (2010) distinguish between two types of problems: • Technological limitations • Perceptual nature • Proposed framework focuses on perceptual issues Martin Knecht

  6. Perceptual Pipeline • Perceptual pipeline used to classify issuesKruijff E., et al. (2010) Environment Capturing AR Framework Augmentation Display Device User Martin Knecht

  7. Capturing / Augmentation Stages • Capturing: Covers the process of converting the optical image to a digital one Kruijff E., et al. (2010) • Image resolution, lens distortion,exposure, color correctness,… • Augmentation: Deals with adding the virtual objects into the augmented sceneKruijff E., et al. (2010) • Registration errors, occlusion, rendering,… Martin Knecht

  8. Framework • Our contribution: • Framework to study photorealistic rendering techniques • Interactive tasks with global illumination • Three different rendering modes • Fast prototyping of experiments (XML) • A pilot study to test framework Martin Knecht

  9. Framework • Differential instant radiosity is used to render the scenes Knecht M., et al. (2010) • Rendering modes can be changed during run-time • Mode A: shadows / indirect illumination • Mode B: shadows / indirect illumination • Mode C: shadows / indirect illumination Martin Knecht

  10. Rendering Mode A • Different rendering modes are supported • No shadows • No indirect illumination Martin Knecht

  11. Rendering Mode B • Different rendering modes are supported • With shadows • No indirect illumination Martin Knecht

  12. Rendering Mode C • Different rendering modes are supported • With shadows • With indirect illumination Martin Knecht

  13. Pilot Study • Pilot study to evaluate our framework • Twenty-one participants (15 male, 6 female) • Age between 19 – 59 • 5 tasks Martin Knecht

  14. Pilot Study • Task 1: Estimate distance between real and virtual cubes Martin Knecht

  15. Pilot Study • Task 2: Place real cube at position of virtual one Martin Knecht

  16. Pilot Study • Task 3: Place virtual cube at position of real one using computer keyboard Martin Knecht

  17. Pilot Study • Task 4: Grab and lift real cube Martin Knecht

  18. Pilot Study • Task 5: Grab and lift virtual cube - real cube was used for tactile feedback Martin Knecht

  19. Pilot Study • Duration: 30 to 60 minutes • Interview followed afterwards • Measured • Distance error for tasks 1, 2, 3 • Time for tasks 2, 3, 4, 5 • Analyzed data using non-parametric Friedman tests • Result: No significant effect of rendering technique found Martin Knecht

  20. Pilot Study Martin Knecht

  21. Pilot Study Martin Knecht

  22. Pilot Study • Distance estimation perceived easier by 6 participants in left/right and height direction than in depth • Although no significant effect was found Martin Knecht

  23. Pilot Study • Participants made heavy use of occlusion cue to place cubes in Task 2 & 3 – (19 out of 20) Martin Knecht

  24. Pilot Study • 7 participants preferred manipulation with a computer keyboard (Task 2 vs. Task 3). Martin Knecht

  25. Limitations • No support for stereo rendering • No distance information of environment • Only video see-through HMDs are supported • Tone-mapping still needs manual fine tuning • No support for mobile devices Martin Knecht

  26. Future Work • Enhance rendering framework • Support for stereo rendering • Add camera artifacts • New studies with new tasks • Tasks without occlusion information • Use chin rest to reduce movement • Design new tasks Martin Knecht

  27. Conclusion • We proposed a research test-bed for perceptual studies – still work in progress • Different rendering modes allow new kind of experiments • We showed the results of a pilot study using our framework Martin Knecht

  28. Thank you for your attention! • What features would you like to have in such a framework? Martin Knecht

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