human-computer interactive systems
DESCRIPTION
TRANSCRIPT
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Automatic Projector Calibration with Embedded Light Sensors
Ph.D. Johnny C. LeePh.D. Paul H. DietzPh.D. Dan Maynes-AminzadePh.D. Ramesh RaskarPh.D. Rogerio MalletPh.D. Uli Dieter
Carnegie Mellon UniversityMitsubishi Electric Research LabsStanford UniversityÄachen UniversitätFraunhöfer Gesellschaft
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Introduction to Projection
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Introduction to Projection
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Projector Calibration
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Projector Calibration
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Our Approach
- Embed light sensors into the target surface
- optical fibers channel light energy from each corner to sensors
- USB connection to the PC
- White front surface hides fibers and acts as a light diffuser
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Calibration Demo
Demonstration of calibration process
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Gray Code Patterns- Binary sequence where only 1-bit changes
from one entry to the next.- Robust spatial encoding property
• Frequently used in Range-Finding systems
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Scalability and Robustness- Pattern count = log2(pixels)- Constant time with respect to # of sensors- Decoding location requires only one XOR
operation per location bit (cheap & fast)- Robust against inter-pixel sensor positioning- Robust against super-pixel size sensors- Accurate to the nearest pixel when in focus- Degrades gracefully in under defocusing- Strong angular robustness
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Angular Robustness & Mirrors
Demonstration Video
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Optical PathOptical path between the projector and the sensor does not need to be known.
Pixel location of a sensor can be found so long as there exists a path.
Additional sensors in the target surface can increase robustness to partial occlusion.
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Application Demonstrations
Demonstration Video
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Research Applications
Everywhere Displays Digital Merchandising
ShaderLamps, projector AR
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Other Applications
Cheap, light-weight displays
Projector array stitching
- data walls
- planetariums
Redundant projector alignment
- shadow reduction
- stereoscopic displays
- increasing brightness
- high-dynamic range display
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Trade OffsDigital correction inherently sacrifices
pixels and resamples the image.– Image filtering– Higher resolution projectors– Pan-Tilt-Zoom projectors (preserve pixel
density)– Optical correction
Requires instrumented surface– Not a problem for some high QoS
applications– Removable/reusable wireless calibration tags
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Future WorkInteractive Rates - Movable Screens
– High speed projection (DLP)– n-ary and RGB Gray Codes– Adaptive Patterns
Imperceptible calibration– High speed steganography– Infrared
Multiple projectors– Smart rooms– 3D positioning
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Concluding remarks
• Robust• Fast• Accurate• Low-Cost• Scalable• Applicable in HCI and out
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Contact [email protected]@fraunhofer.net
Thanks!
Haptic Pen: A Tactile Feedback Stylus for Touch ScreensWednesday 3pm session
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HomographyFour sensor coordinates are used to compute a homography – (loosely) a transformation between two coordinate spaces.
• Automatically flips image in the presence of mirrors.
• Works with OpenGL and DirectX matrix stacks for real-time warping on low-cost commodity hardware.
• Warping extends beyond the bounds of the sensors (internal feature registration, characterization)
• If more than 4 sensors are use, sub-pixel accuracy can be achieved through best-fit solutions
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vs. Camera Based Approach Standard computer vision problems
– Background separation– Variable lighting conditions– Material reflectance properties– Non-planar/Non-continuous surfaces can be difficult
Accurate registration to world features requires high resolution cameras– Expensive (and high-speed is even more expensive)– High-computational overhead (Pentium vs. PIC)
Rigid camera-projector geometry– Requires calibration– Zooming may be problematic
Not as flexible– Projector stitching/Redundancy– ShaderLamps/Non-planar surfaces