Enhanced contrast for object detection and characterization by optical imaging based on differences between images

• US 9,934,580 B2
• Filed: 05/03/2017
• Issued: 04/03/2018
• Est. Priority Date: 01/17/2012
• Status: Active Grant

• Current Assignee: Lmi Liquidating Co., LLC
• Original Assignee: Leap Motion Incorporated (Ultraleap Limited)
• Inventors: Holz, David S., Yang, Hua
• Primary Examiner(s): Park, Chan
• Assistant Examiner(s): Thomas, Mia M
• Application Number:
  US15/586,048
• Publication Number:
  US 20170236293A1
• Time in Patent Office: 335 Days
• CPC Class Codes: G06F 3/017 Gesture based interaction, e.g. based on a set of recognized hand gestures interaction based on gestures traced on a digitiser G06F3/04883
• CPC Class Codes: G06F 3/0304 Detection arrangements using opto-electronic means constructional details of pointing devices not related to the detection arrangement using opto-electronic means G06F3/033; optical digitisers G06F3/042
• CPC Class Codes: G06T 2200/04 involving 3D image data
• CPC Class Codes: G06T 2207/10012 Stereo images
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 7/10 Segmentation; Edge detection motion-based segmentation G06T7/215
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/194 involving foreground-background segmentation
• CPC Class Codes: G06T 7/215 Motion-based segmentation
• CPC Class Codes: G06T 7/248 involving reference images or patches
• CPC Class Codes: G06T 7/251 involving models
• CPC Class Codes: G06T 7/254 involving subtraction of images
• CPC Class Codes: G06T 7/262 using transform domain methods, e.g. Fourier domain methods
• CPC Class Codes: G06T 7/344 involving models
• CPC Class Codes: G06T 7/37 using transform domain methods
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: G06V 20/64 Three-dimensional objects
• CPC Class Codes: G06V 40/107 Static hand or arm
• CPC Class Codes: H04N 13/254 in combination with electromagnetic radiation sources for illuminating objects
• CPC Class Codes: H04N 23/661 : Transmitting camera control signals through networks, e.g. control via the Internet

Abstract

Enhanced contrast between an object of interest and background surfaces visible in an image is provided using controlled lighting directed at the object. Exploiting the falloff of light intensity with distance, a light source (or multiple light sources), such as an infrared light source, can be positioned near one or more cameras to shine light onto the object while the camera(s) capture images. The captured images can be analyzed to distinguish object pixels from background pixels.

Claims

1. A method of capturing and analyzing an image, the method comprising:

utilizing an image analyzer coupled to at least one camera and at least one light source to;

operate the at least one camera to capture a sequence of images including a first image captured at a time when the at least one light source is illuminating a field of view;

identify pixels corresponding to an object of interest rather than to a background;

based on the identified pixels, construct a 3D model of the object of interest, including a position and shape of the object of interest; and

distinguish between (i) foreground image components corresponding to objects located within a proximal zone of the field of view, the proximal zone extending from the at least one camera and having a depth relative thereto of at least twice an expected maximum distance between the objects corresponding to the foreground image components and the at least one camera, and (ii) background image components corresponding to objects located within a distal zone of the field of view, the distal zone being located, relative to the at least one camera, beyond the proximal zone.

2. The method of claim 1, wherein the proximal zone has a depth of at least four times the expected maximum distance.

3. The method of claim 1, wherein the at least one light source is a diffuse emitter.

4. The method of claim 3, wherein the at least one light source is an infrared light-emitting diode and the at least one camera is an infrared-sensitive camera.

5. The method of claim 1, wherein at least two light sources flank the at least one camera and are substantially coplanar therewith.

6. The method of claim 1, wherein the at least one camera and the at least one light source are oriented vertically upward or horizontally outward.

7. The method of claim 1, wherein the image analyzer controls the at least one camera to provide an exposure time no greater than 100 microseconds and wherein the image analyzer activates the at least one light source during the exposure time at a power level of at least 5 watts.

8. The method of claim 1, wherein a holographic diffraction grating is positioned between a lens of the at least one camera and the field of view.

9. The method of claim 1, wherein the image analyzer is further configured to operate the at least one camera to capture second and third images when the at least one light source is not illuminating the field of view and identify the pixels corresponding to the object of interest based on a difference between the first and second images and a difference between the first and third images, and wherein the second image is captured before the first image and the third image is captured after the second image.

10. A wearable goggle, comprising:

at least one camera oriented toward a field of view containing a background and a hand including fingers;

at least one light source disposed on a same side of the field of view as the camera and oriented to illuminate the field of view; and

a processor coupled to the at least one camera and the light source and configured to;

activate at least one light source to illuminate the field of view containing the hand;

capture a sequence of digital images of the field of view using the at least one camera at a time when the at least one light source is activated;

identify pixels corresponding to the hand rather than to the background; and

based on the identified pixels, constructing a 3D model of the hand, including a position and shape of the hand,

wherein the at least one light source is positioned such that the hand is located within a proximal zone of the field of view, the proximal zone extending from the at least one camera to a distance at least twice an expected maximum distance between the hand and the at least one camera.

11. The wearable goggle of claim 10 wherein the proximal zone has a depth of at least four times the expected maximum distance.

12. The wearable goggle of claim 10 wherein the at least one light source is a diffuse emitter.

13. The wearable goggle of claim 10 wherein the at least one light source is an infrared light-emitting diode and the at least one camera is an infrared-sensitive camera.

14. The wearable goggle of claim 10 wherein at least two light sources are activated, and the at least two light sources flank the at least one camera and are substantially coplanar therewith.

15. The wearable goggle of claim 10 wherein the at least one camera and the at least one light source are oriented horizontally outward with respect to a wearable goggle.

16. A wearable goggle, comprising:

at least one camera oriented toward a field of view containing a background and a hand including fingers;

at least one light source disposed on a same side of the field of view as the camera and oriented to illuminate the field of view; and

a processor coupled to the at least one camera and the light source and configured to;

activate the at least one light source to illuminate the field of view containing the hand;

capture a sequence of digital images of the field of view using that at least one camera at a time when the at least one light source is activated;

identify pixels corresponding to the hand rather than to the background;

based on the identified pixels, construct a 3D model of the hand, including a position and shape of the hand; and

capture a first image when the at least one light source is not activated, a second image when the at least one light source is activated, and a third image when the at least one light source is not activated, wherein pixels corresponding to the hand are identified based on a difference between the second and first images and a difference between the second and third images.