Automatic Projector Calibration with Embedded Light Sensors Ph.D. Johnny C. Lee Ph.D. Paul H. Dietz Ph.D. Dan Maynes-Aminz...
Introduction to Projection
Introduction to Projection
Projector Calibration
Projector Calibration
Our Approach <ul><li>- Embed light sensors into the target surface </li></ul><ul><li>optical fibers channel light energy f...
Calibration Demo Demonstration of calibration process
Gray Code Patterns <ul><li>Binary sequence where only 1-bit changes from one entry to the next. </li></ul><ul><li>Robust s...
  Binary  Gray 0000 0001 0010 0011 0100 0101 0110 0111 1000 1001 1010 1011 1100 1101 1110 1111 0000 0001 0011 0010 0110 01...
  Binary  Gray 0000 0001 0010 0011 0100 0101 0110 0111 1000 1001 1010 1011 1100 1101 1110 1111 0000 0001 0011 0010 0110 01...
  Binary  Gray
  Binary  Gray
  Binary  Gray
  Binary  Gray
  Binary  Gray
  Binary  Gray
  Binary  Gray
  Binary  Gray
  Binary  Gray
  Binary  Gray
  Binary  Gray
  Binary  Gray
Scalability and Robustness <ul><li>Pattern count = log 2 (pixels) </li></ul><ul><li>Constant time with respect to # of sen...
Angular Robustness & Mirrors Demonstration Video
Optical Path Optical path between the projector and the sensor does not need to be known. Pixel location of a sensor can b...
Application Demonstrations Demonstration Video
Research Applications Everywhere Displays Digital Merchandising ShaderLamps, projector AR
Other Applications <ul><li>Cheap, light-weight displays </li></ul><ul><li>Projector array stitching </li></ul><ul><li>data...
Trade Offs <ul><li>Digital correction inherently sacrifices pixels and resamples the image. </li></ul><ul><ul><li>Image fi...
Future Work <ul><li>Interactive Rates - Movable Screens </li></ul><ul><ul><li>High speed projection (DLP) </li></ul></ul><...
Concluding remarks <ul><li>Robust </li></ul><ul><li>Fast </li></ul><ul><li>Accurate </li></ul><ul><li>Low-Cost </li></ul><...
<ul><li>Contact Info </li></ul><ul><li>[email_address] </li></ul><ul><li>[email_address] </li></ul>Thanks!   Haptic Pen: A...
Homography <ul><li>Automatically flips image in the presence of mirrors. </li></ul><ul><li>Works with OpenGL and DirectX m...
vs. Camera Based Approach <ul><li>Standard computer vision problems </li></ul><ul><ul><li>Background separation </li></ul>...
Upcoming SlideShare
Loading in …5
×

Human-Computer Interactive Systems

998 views

Published on

Published in: Education
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
998
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
11
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Human-Computer Interactive Systems

  1. 1. Automatic Projector Calibration with Embedded Light Sensors Ph.D. Johnny C. Lee Ph.D. Paul H. Dietz Ph.D. Dan Maynes-Aminzade Ph.D. Ramesh Raskar Ph.D. Rogerio Mallet Ph.D. Uli Dieter Carnegie Mellon University Mitsubishi Electric Research Labs Stanford University Äachen Universität Fraunhöfer Gesellschaft
  2. 2. Introduction to Projection
  3. 3. Introduction to Projection
  4. 4. Projector Calibration
  5. 5. Projector Calibration
  6. 6. Our Approach <ul><li>- Embed light sensors into the target surface </li></ul><ul><li>optical fibers channel light energy from each corner to sensors </li></ul><ul><li>USB connection to the PC </li></ul><ul><li>White front surface hides fibers and acts as a light diffuser </li></ul>
  7. 7. Calibration Demo Demonstration of calibration process
  8. 8. Gray Code Patterns <ul><li>Binary sequence where only 1-bit changes from one entry to the next. </li></ul><ul><li>Robust spatial encoding property </li></ul><ul><ul><li>Frequently used in Range-Finding systems </li></ul></ul>
  9. 9. Binary Gray 0000 0001 0010 0011 0100 0101 0110 0111 1000 1001 1010 1011 1100 1101 1110 1111 0000 0001 0011 0010 0110 0111 0101 0100 1100 1101 1111 1110 1010 1011 1001 1000
  10. 10. Binary Gray 0000 0001 0010 0011 0100 0101 0110 0111 1000 1001 1010 1011 1100 1101 1110 1111 0000 0001 0011 0010 0110 0111 0101 0100 1100 1101 1111 1110 1010 1011 1001 1000
  11. 11. Binary Gray
  12. 12. Binary Gray
  13. 13. Binary Gray
  14. 14. Binary Gray
  15. 15. Binary Gray
  16. 16. Binary Gray
  17. 17. Binary Gray
  18. 18. Binary Gray
  19. 19. Binary Gray
  20. 20. Binary Gray
  21. 21. Binary Gray
  22. 22. Binary Gray
  23. 23. Scalability and Robustness <ul><li>Pattern count = log 2 (pixels) </li></ul><ul><li>Constant time with respect to # of sensors </li></ul><ul><li>Decoding location requires only one XOR operation per location bit (cheap & fast) </li></ul><ul><li>Robust against inter-pixel sensor positioning </li></ul><ul><li>Robust against super-pixel size sensors </li></ul><ul><li>Accurate to the nearest pixel when in focus </li></ul><ul><li>Degrades gracefully in under defocusing </li></ul><ul><li>Strong angular robustness </li></ul>
  24. 24. Angular Robustness & Mirrors Demonstration Video
  25. 25. Optical Path Optical 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.
  26. 26. Application Demonstrations Demonstration Video
  27. 27. Research Applications Everywhere Displays Digital Merchandising ShaderLamps, projector AR
  28. 28. Other Applications <ul><li>Cheap, light-weight displays </li></ul><ul><li>Projector array stitching </li></ul><ul><li>data walls </li></ul><ul><li>planetariums </li></ul><ul><li>Redundant projector alignment </li></ul><ul><li>shadow reduction </li></ul><ul><li>stereoscopic displays </li></ul><ul><li>increasing brightness </li></ul><ul><li>- high-dynamic range display </li></ul>
  29. 29. Trade Offs <ul><li>Digital correction inherently sacrifices pixels and resamples the image. </li></ul><ul><ul><li>Image filtering </li></ul></ul><ul><ul><li>Higher resolution projectors </li></ul></ul><ul><ul><li>Pan-Tilt-Zoom projectors (preserve pixel density) </li></ul></ul><ul><ul><li>Optical correction </li></ul></ul><ul><li>Requires instrumented surface </li></ul><ul><ul><li>Not a problem for some high QoS applications </li></ul></ul><ul><ul><li>Removable/reusable wireless calibration tags </li></ul></ul>
  30. 30. Future Work <ul><li>Interactive Rates - Movable Screens </li></ul><ul><ul><li>High speed projection (DLP) </li></ul></ul><ul><ul><li>n-ary and RGB Gray Codes </li></ul></ul><ul><ul><li>Adaptive Patterns </li></ul></ul><ul><li>Imperceptible calibration </li></ul><ul><ul><li>High speed steganography </li></ul></ul><ul><ul><li>Infrared </li></ul></ul><ul><li>Multiple projectors </li></ul><ul><ul><li>Smart rooms </li></ul></ul><ul><ul><li>3D positioning </li></ul></ul>
  31. 31. Concluding remarks <ul><li>Robust </li></ul><ul><li>Fast </li></ul><ul><li>Accurate </li></ul><ul><li>Low-Cost </li></ul><ul><li>Scalable </li></ul><ul><li>Applicable in HCI and out </li></ul>
  32. 32. <ul><li>Contact Info </li></ul><ul><li>[email_address] </li></ul><ul><li>[email_address] </li></ul>Thanks!   Haptic Pen: A Tactile Feedback Stylus for Touch Screens Wednesday 3pm session
  33. 33. Homography <ul><li>Automatically flips image in the presence of mirrors. </li></ul><ul><li>Works with OpenGL and DirectX matrix stacks for real-time warping on low-cost commodity hardware. </li></ul><ul><li>Warping extends beyond the bounds of the sensors (internal feature registration, characterization) </li></ul><ul><li>If more than 4 sensors are use, sub-pixel accuracy can be achieved through best-fit solutions </li></ul>Four sensor coordinates are used to compute a homography – (loosely) a transformation between two coordinate spaces.
  34. 34. vs. Camera Based Approach <ul><li>Standard computer vision problems </li></ul><ul><ul><li>Background separation </li></ul></ul><ul><ul><li>Variable lighting conditions </li></ul></ul><ul><ul><li>Material reflectance properties </li></ul></ul><ul><ul><li>Non-planar/Non-continuous surfaces can be difficult </li></ul></ul><ul><li>Accurate registration to world features requires high resolution cameras </li></ul><ul><ul><li>Expensive (and high-speed is even more expensive) </li></ul></ul><ul><ul><li>High-computational overhead (Pentium vs. PIC) </li></ul></ul><ul><li>Rigid camera-projector geometry </li></ul><ul><ul><li>Requires calibration </li></ul></ul><ul><ul><li>Zooming may be problematic </li></ul></ul><ul><li>Not as flexible </li></ul><ul><ul><li>Projector stitching/Redundancy </li></ul></ul><ul><ul><li>ShaderLamps/Non-planar surfaces </li></ul></ul>

×