Near touch interaction with structured light

• US 9,323,395 B2
• Filed: 01/20/2015
• Issued: 04/26/2016
• Est. Priority Date: 02/10/2011
• Status: Active Grant

• Current Assignee: Golden Edge Holding Corporation
• Original Assignee: Edge Technologies, Inc
• Inventors: El Dokor, Tarek
• Primary Examiner(s): Xiao, Ke
• Assistant Examiner(s): Imperial, Jed-Justin
• Application Number:
  US14/600,032
• Publication Number:
  US 20150130803A1
• Time in Patent Office: 462 Days
• Field of Search: 345/423, 345/426, 345/642, 345157-158, 345/173, 382106-107, 382/282
• US Class Current: 1/1
• 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 3/0421 by interrupting or reflecting a light beam, e.g. optical touch-screen
• CPC Class Codes: G06T 2200/04 involving 3D image data
• CPC Class Codes: G06T 2207/10021 Stereoscopic video; Stereoscopic image sequence
• CPC Class Codes: G06T 7/521 from laser ranging, e.g. using interferometry; from the projection of structured light
• CPC Class Codes: G06T 7/593 from stereo images

Abstract

A near-touch interface is provided that utilizes stereo cameras and a series of targeted structured light tessellations, emanating from the screen as a light source and incident on objects in the field-of-view. After radial distortion from a series of wide-angle lenses is mitigated, a surface-based spatio-temporal stereo algorithm is utilized to estimate initial depth values. Once these values are calculated, a subsequent refinement step may be applied in which light source tessellations are used to flash a structure onto targeted components of the scene, where initial near-interaction disparity values have been calculated. The combination of a spherical stereo algorithm, and smoothing with structured light source tessellations, provides for a very reliable and fast near-field depth engine, and resolves issues that are associated with depth estimates for embedded solutions of this approach.

Claims

1. A system for determining near touch interaction, comprising:

a display for displaying one or more elements thereon;

one or more stereo camera pairs positioned adjacent to the display; and

a processor for causing the display to flash one or more structured light sequences using the light sources that illuminate the display on a user pointer placed adjacent to the display, determining a depth map in accordance with information acquired by the stereo camera pair, and if desired, employing the one or more structured light sequences to possibly refine the depth map, wherein the display produces patterns targeting only regions of the field-of view where the depth refinement is determined to be beneficial, and determining a location corresponding to one or more of the one or more elements displayed on the display to be selected in accordance with the determined depth map.

2. The system of claim 1, further comprising one or more appropriate lenses to produce a shallow depth of field highlighting the user pointer closer to the field of view.

3. The system of claim 1, wherein the use of the shallow depth of field results in a blurred background.

4. The system of claim 1, where in the structured light is displayed on only one or more predetermined portions of the display.

5. The system of claim 4, wherein the structured light is directed at a predetermined portion of a field of view of the display.

6. The system of claim 1, wherein the structured light is provided by an image displayed on the display.

7. The system of claim 1, wherein information acquired by the one or more stereo camera pairs is dewarped.

8. The system of claim 1, wherein the processor is located remotely.

9. The system of claim 8, wherein the processor is located in a cloud computing environment.

10. A method for determining near touch interaction by a user object, comprising the steps of:

displaying on a display one or more objects;

acquiring one or more images of the user object by one or more pairs of stereo cameras located adjacent to the display;

dewarping the one or more acquired images;

computing a disparity based upon the dewarped images;

identifying one or more target regions of the display adjacent to one or more corresponding portions of the disparity that may benefit from refinement, and displaying one or more screen tessellations therein using the light sources that illuminate the display, wherein the display produces patterns targeting only regions of the field-of view where the depth refinement is determined to be beneficial;

refining the computed disparity in accordance with additional data received in accordance with the displayed screen tessellations; and

determining one or more of the displayed objects to be selected by the user object in accordance with the redefined computer disparity.

11. The method of claim 10, wherein the one or more acquired images comprise a left and right image acquired at a substantially simultaneous time.

12. The method of claim 11, wherein the displaying of screen tessellations further comprises the step of flashing one or more structured light sequences on a targeted portion of the user object positioned adjacent to the display.

13. The system of claim 12, wherein the structured light is a targeted structured light.

14. The system of claim 13, where in the structured light is displayed on only one or more predetermined portions of the display.

15. The system of claim 13, wherein the structured light emanates from the display'"'"'s pixels.

16. The system of claim 10, wherein the user object is a finger of the user.

17. The system of claim 10, wherein the light is adaptive, such that it is brighter when ambient light is greater and darker when ambient light is less.

18. The method of claim 10, wherein the patterns that are produced vary in one or more of size, location, orientation, or frequency, depending on the size and depth of the targeted region.

19. The method of claim 10, wherein the tessellations are interleaved with the actual data, allowing the system to display the structured light without the light being perceived by the user.

20. The system of claim 10, wherein the one or more pairs of stereo cameras cover both the visible range and infrared ranges.

21. The system of claim 20, wherein if it is determined that the light source is strong enough, the infrared sensors are disregarded.

22. The method of claim 10, wherein the one or more pairs of stereo cameras are dual band, covering substantially both of the visible range and infrared range.

23. The method of claim 10, wherein the one or more stereo pairs comprise lenses that are able to properly display objects that are closer to the cameras in the field of view.

24. The method of claim 10, wherein the one or more stereo pairs comprise lenses that play the role of multiple bandpass filters to allow and block different frequencies of the lighting spectrum.

25. A computer program stored on a non-transitory computer medium, the computer program causing a processor to implement an API to perform the steps of:

generating or refining a coarse depth map;

determining one or more critical data points to assist in refining the coarse depth map;

providing control over fine-tuning one or more light tessellations to be displayed on at least a portion of a display using the light sources that illuminate the display to aid in acquisition of the one or more critical data points, wherein the display produces patterns of the tessellations targeting only regions of the field-of view where the depth refinement is determined to be beneficial; and

performing scene recognition and analysis in accordance with one or more artificial intelligence algorithms based upon the coarse depth map as refined in accordance with the acquired one or more critical data points.