METHOD FOR CALIBRATING AN INTERACTIVE INPUT SYSTEM AND INTERACTIVE INPUT SYSTEM EXECUTING THE CALIBRATION METHOD

• US 20100079385A1
• Filed: 09/29/2008
• Published: 04/01/2010
• Est. Priority Date: 09/29/2008
• Status: Abandoned Application

• Current Assignee: Smart Technologies ULC (Hon Hai Precision Industry Co., Ltd.)
• Original Assignee: Smart Technologies ULC (Hon Hai Precision Industry Co., Ltd.)
• Inventors: HOLMGREN, DAVID E., Clarke, George, Wang, Yunqui Rachel, Wright, Joe, McGibney, Grant, Sirotich, Roberto A.L., Tse, Edward
• Application Number:
  US12/240,963
• Publication Number:
  US 20100079385A1
• Time in Patent Office: Days
• US Class Current: 345/173
• CPC Class Codes: G06F 2203/04109 FTIR in optical digitiser, i.e. touch detection by frustrating the total internal reflection within an optical waveguide due to changes of optical properties or deformation at the touch location
• CPC Class Codes: G06F 3/0418 for error correction or compensation, e.g. based on parallax, calibration or alignment
• CPC Class Codes: G06F 3/0425 using a single imaging device like a video camera for tracking the absolute position of a single or a plurality of objects with respect to an imaged reference surface, e.g. video camera imaging a display or a projection screen, a table or a wall surface, on which a computer generated image is displayed or projected tracking a projected light spot to determine a position on a display surface G06F3/0386

Abstract

A method of calibrating an interactive input system comprises receiving images of a calibration video presented on a touch panel of the interactive input system. A calibration image is created based on the received images, and features are located in the calibration image. A transformation between the touch panel and the received images is determined based on the located features and corresponding features in the calibration video.

Claims

19. An interactive input system comprising a touch panel and processing structure executing a calibration method, said calibration method determining a transformation between the touch panel and an imaging plane based on known features in a calibration video presented on the touch panel and features located in a calibration image created based on received images of the calibration video.

20. A computer readable medium embodying a computer program for calibrating an interactive input device, the computer program comprising:

computer program code receiving images of a calibration video presented on a touch panel of the interactive input system;

computer program code creating a calibration image based on the received images;

computer program code locating features in the calibration image; and

computer program code determining a transformation between the touch panel and the received images based on the located features and corresponding features in the calibration video.

21. A method for determining one or more touch points in a captured image of a touch panel in an interactive input system, comprising:

creating a similarity image based on the captured image and an image of the touch panel without any touch points;

creating a thresholded image by thresholding the similarity image based on an adaptive threshold;

identifying one or more touch points as areas in the thresholded image;

refining the bounds of the one or more touch points based on pixel intensities in corresponding areas in the similarity image.

1. A method of calibrating an interactive input system, comprising:

receiving images of a calibration video presented on a touch panel of the interactive input system;

creating a calibration image based on the received images;

locating features in the calibration image; and

determining a transformation between the touch panel and the received images based on the located features and corresponding features in the calibration video.

2. The method of claim 1, wherein the calibration video comprises a set of frames with a checkerboard pattern and a set of frames with an inverse checkerboard pattern.

3. The method of claim 2, wherein creating a calibration image comprises:

creating a mean checkerboard image based on received images of the checkerboard pattern;

creating a mean inverse checkerboard image based on received images of the inverse checkerboard pattern; and

creating a difference image as the difference between the mean checkerboard image and the mean inverse checkerboard image.

4. The method of claim 3, wherein received images of the checkerboard pattern are distinguished from received images of the inverse checkerboard pattern based on the pixel intensity at a selected location in the received images.

5. The method of claim 4, further comprising selecting received images for creating the mean and mean inverse checkerboard images based on the pixel intensity at the selected location in respective received images being above or below an intensity range.

6. The method of claim 3, further comprising thresholding pixels in the selected received images as either black or white pixels.

7. The method of claim 3, wherein the located features are intersection points of lines common to the checkerboard and inverse checkerboard patterns.

8. The method of claim 7, wherein the lines are identified as peaks in a Radon transform of the calibration image.

9. The method of claim 8, wherein the intersection points are identified based on vector products of the identified lines.

10. The method of claim 1, wherein creating a calibration image comprises:

creating a mean calibration image based on the received images; and

performing a smoothing, edge-preserving procedure to remove noise from the mean calibration image.

11. The method of claim 10, wherein the smoothing, edge-preserving procedure is an anisotropic diffusion procedure.

12. The method of claim 10, wherein the smoothing, edge-preserving procedure is a median filtering.

13. The method of claim 10, wherein creating a calibration image further comprises performing lens distortion correction on the mean calibration image.

14. The method of claim 13, wherein the lens distortion correction is based on predetermined lens distortion parameters.

15. The method of claim 11, wherein creating a calibration image comprises creating an edge image.

16. The method of claim 15, wherein creating the calibration image further comprises filtering the edge image to preserve prominent edges.

17. The method of claim 16, wherein the filtering comprises performing non-maximum suppression to the edge image.

18. The method of claim 3, further comprising cropping the difference image.

23. The method of claim 21, wherein the similarity image is smoothed prior to creating the thresholded image.

24. The method of claim 23, further comprising mapping each touch point center coordinate to a display coordinate.

25. The method of claim 21, further comprising prior to creating a similarity image, transforming the captured image and the background image to a display coordinate system and to correct for lens distortion.

23-1. The method of claim 21, further comprising characterizing each touch point as an ellipse having center coordinates.

26. An interactive input system comprising a touch panel and processing structure executing a touch point determination method, said touch point determination method determining one or more touch points in a captured image of the touch panel as areas identified in a thresholded similarity image refined using pixel intensities in corresponding areas in the similarity image.

27. A computer readable medium embodying a computer program for determining one or more touch points in a captured image of a touch panel in an interactive input system, the computer program comprising:

computer program code creating a similarity image based on the captured image and an image of the touch panel without any touch points;

computer program code creating a thresholded image by thresholding the similarity image based on an adaptive threshold;

computer program code identifying one or more touch points as areas in the thresholded image;

computer program code refining the bounds of the one or more touch points based on pixel intensities in corresponding areas in the similarity image.