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QUASID: Quantifying 3D Image Perception in VR

Ferdi Smit Center for Mathematics and Computer Science (CWI) Amsterdam. QUASID: Quantifying 3D Image Perception in VR. Why quantify image perception?. QUASID: Quantify Interaction Evaluate/improve 3D input-devices Hypothesis: Improved perceived 3D images  Improved 3D interaction

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QUASID: Quantifying 3D Image Perception in VR

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  1. Ferdi Smit Center for Mathematics and Computer Science (CWI) Amsterdam QUASID:Quantifying 3D Image Perceptionin VR

  2. Why quantify image perception? • QUASID: Quantify Interaction • Evaluate/improve 3D input-devices • Hypothesis: • Improved perceived 3D images  Improved 3D interaction • Challenge: • Subjective quality of 3D images/animations • How to measure/quantify?

  3. Example: Crosstalk Reduction • Left: Crosstalk ghost image in 3D stereo-viewing • Right: Crosstalk reduction algorithm applied • Which is better? How much better? • [Non-uniform Crosstalk Reduction for Dynamic Scenes, IEEE-VR 2007]

  4. Crosstalk Evaluation: Data • Photographs of the display • Through the shutter glasses • What the user sees • Compare photographs to evaluate differences • Per-pixel comparison (RMSE) useless

  5. Crosstalk Evaluation: VDP • Need perceptual comparison • Existing software: Visible Differences Predictor[Daly90] • Measure percentage of perceptually different pixels • How different is different? • Compare different pixels in perceptual color space • [Three Extensions to Subtractive Crosstalk Reduction, EGVE 2007 (to appear)]

  6. Example: Effects of Motion • Motion can cause ‘judder’: • Visible double-image artifacts • Perceived jerky motion • Extrapolate motion field • Results in smooth perceived motion • Eliminates perceptual artifacts • [The Design and Implementation of a VR-Architecture for Smooth Motion, submitted to VRST 2007]

  7. Example: Effects of Motion • Judder reduction: • Increased feeling of system responsiveness • Lower perceived latency • Better interaction? • How to measure improvement? • Only still image comparisons • Need to quantify temporal perception! How?

  8. Open Questions • We can now determine: • which algorithm is perceptually better … • … and by how much • However: • What about animations and temporal perception? • How is interaction influenced by better images?

  9. Current Status • Crosstalk papers published: • Non-Uniform Crosstalk Reduction for Dynamic Scenes, IEEE-VR 2007 • Three Extensions to Subtractive Crosstalk Reduction, EGVE 2007 (to appear) • Other Work: • GraphTracker: A Topology Projection Invariant Optical Tracker, EGVE 2006, and Computers and Graphics Feb. 2007 • The Design and Implementation of a VR-Architecture for Smooth Motion, Submitted to VRST 2007

  10. The End • Thank you for your attention. • Questions / Suggestions ?

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