Interactive input system and method

• US 8,600,107 B2
• Filed: 03/31/2011
• Issued: 12/03/2013
• Est. Priority Date: 03/31/2011
• Status: Active Grant

• 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
• Primary Examiner(s): Bella, Matthew
• Assistant Examiner(s): HEIDEMANN, JASON E
• Application Number:
  US13/077,637
• Publication Number:
  US 20120250936A1
• Time in Patent Office: 978 Days
• Field of Search: None
• US Class Current: 382/103
• CPC Class Codes: G06F 2203/04104 Multi-touch detection in digitiser, i.e. details about the simultaneous detection of a plurality of touching locations, e.g. multiple fingers or pen and finger
• CPC Class Codes: G06F 2203/04108 Touchless 2D- digitiser, i.e. digitiser detecting the X/Y position of the input means, finger or stylus, also when it does not touch, but is proximate to the digitiser's interaction surface without distance measurement in the Z direction
• CPC Class Codes: G06F 3/042 by opto-electronic means

Abstract

A method of determining locations of at least two pointers in a captured image frame comprises generating a vertical intensity profile (VIP) from the captured image frame, the VIP comprising peaks generally corresponding to the at least two pointers; determining if the peaks are closely spaced and, if the peaks are closely spaced, fitting a curve to the VIP; analyzing the fitted curve to determine peak locations of the fitted curve; and registering the peak locations as the pointer locations.

Claims

1. A method of determining locations of at least two pointers in a captured image frame, the method comprising:

generating a vertical intensity profile (VIP) from the captured image frame, the VIP comprising peaks generally corresponding to the at least two pointers;

determining if the peaks are closely spaced and, if the peaks are closely spaced;

fitting a curve to the VIP by calculating a nonlinear least squares fit for at least one model, each model comprising at least two peaks, each peak having at least one of a respective peak location, a respective peak half-width and a respective peak amplitude, calculating a goodness-of-fit value for each model and determining a final model by comparing the goodness-of-fit values, the final model being said fitted curve;

analyzing the fitted curve to determine peak locations of the fitted curve; and

registering the determined peak locations as the pointer locations.

2. The method of claim 1, wherein if the peaks are determined not to be closely spaced, the method further comprising:

analyzing the VIP to determine the peak locations; and

registering the determined peak locations as the pointer locations.

3. The method of claim 1, wherein the nonlinear least squares fit is calculated using one of a conjugate gradient algorithm, a Levenberg-Marquardt algorithm, and a nonlinear simplex algorithm.

4. The method of claim 1, wherein the fitting a curve further comprises:

calculating an Akaike Information Criterion (AIC) value for each model; and

determining the final model by comparing the goodness-of-fit values and the AIC values.

5. The method of claim 4, wherein the final model determined is the model having at least one of a lowest goodness-of-fit value and a lowest AIC value.

6. The method of claim 5, further comprising:

calculating a value of fit residuals for each model,

wherein the AIC value for each model is calculated based on the value of the fit residuals.

7. The method of claim 1, wherein the at least one model is based on a point-by-point maximum of the VIP, the point-by-point maximum given by:

max([ƒ

(x_o, w, σ

), g(x_o, w, σ

), h(x_o, w, σ

), . . . ])

where ƒ

(x, w, σ

), g(x, w, σ

) and h (x, w, σ

) each represent an individual VIP function corresponding to a respective VIP peak, and where x_o is the peak location and w is the half-width of each individual VIP function, and σ

is instrumental profile width.

8. The method of claim 7, wherein each VIP peak is proportional to an error function erƒ

(x) given by;

9. The method of claim 1, further comprising, prior to said determining:

comparing the VIP to a threshold; and

identifying the peaks in the VIP based on the comparing.

10. An interactive input system, comprising:

at least one imaging assembly capturing image frames of a region of interest; and

processing structure in communication with the at least one imaging assembly, the processing structure being configured to;

generate a vertical intensity profile (VIP) from a captured image frame, the VIP comprising peaks generally corresponding to locations of at least two pointers in the captured image frame; and

determine if the peaks are closely spaced, and if the peaks are closely spaced to;

fit a curve to the VIP by calculating a nonlinear least squares fit for at least one model, each model comprising at least two peaks, each peak having at least one of a respective peak location, a respective peak half-width and a respective peak amplitude, calculating a goodness-of-fit value for each model, and determining a final model by comparing the goodness-of-fit values, the final model being the fitted curve;

analyze the fitted curve to determine peak locations of the fitted curve;

register the determined peak locations as the pointer locations.

11. The system of claim 10, wherein the at least one imaging assembly comprises two or more imaging assemblies, the processing structure being further configured to carry out said generating and said determining for a respective image frame captured by each imaging assembly, and to:

calculate the positions of the at least two pointers by triangulation based on the pointer locations.

12. The system of claim 11, wherein if the peaks are determined not to be closely spaced, the processing structure is further configured to:

analyze the VIP to determine the peak locations; and

register the determined peak locations as the pointer locations.

13. The system of claim 11, wherein the nonlinear least squares fit is calculated using one of a conjugate gradient algorithm, a Levenberg-Marquardt algorithm, and a nonlinear simplex algorithm.

14. The system of claim 11, wherein, during the fitting, the processing structure is further configured to:

calculate an Akaike Information Criterion (AIC) value for each model; and

determine the final model by comparing the goodness-of-fit values and the AIC values.

15. The system of claim 14, wherein the final model determined is the model having at least one of a lowest goodness-of-fit value and a lowest AIC value.

16. The system of claim 15, wherein the processing structure is further configured to:

calculate a value of fit residuals for each model,

wherein the AIC value for each model is calculated based on the value of the fit residuals.

17. The system of claim 11, wherein the at least one model is based on a point-by-point maximum of the VIP, the point-by-point maximum given by:

max([ƒ

(x_o, w, σ

), g(x_o, w, σ

), h(x_o, w, σ

) , . . . ])

where ƒ

(x, w, σ

), g (x, w, σ

) and h (x, w, σ

) each represent an individual VIP function corresponding to a respective VIP peak, and where x_o is the peak location and w is the half-width of each individual VIP function, and σ

is instrumental profile width.

18. The system of claim 17, wherein each VIP peak is proportional to an error function erƒ

(x) given by;

19. The system of claim 11, wherein the processing structure is further configured to, prior to the determining:

compare the VIP to a threshold; and

identify the peaks in the VIP based on the comparing.

20. A non-transitory computer readable medium having embodied thereon a computer program for determining locations of at least two pointers in a captured image frame, the computer program comprising:

program code for generating a vertical intensity profile (VIP) from the captured image frame, the VIP comprising peaks generally corresponding to the at least two pointers; and

program code for determining if the peaks are closely spaced and, if the peaks are closely spaced;

program code for fitting a curve to the VIP by calculating a nonlinear least squares fit for at least one model, each model comprising at least two peaks, each peak having at least one of a respective peak location, a respective peak half-width and a respective peak amplitude, calculating a goodness-of-fit value for each model and determining a final model by comparing the goodness-of-fit values, the final model being said fitted curve;

program code for analyzing the fitted curve to determine peak locations of the fitted curve; and

program code for registering the determined peak locations as the pointer locations.