Enhanced contrast for object detection and characterization by optical imaging based on differences between images
First Claim
Patent Images
1. A method identifying a hand by analyzing captured images, the method comprising:
- activating at least one light source to illuminate a field of view containing a background and the hand including fingers;
operating a camera to capture a plurality of digital images including a first digital image captured at a time when the at least one light source is illuminating the field of view;
identifying pixels of the plurality of digital images that correspond to fingers of the hand that are visible in the plurality of digital images rather than to the background, the identifying including;
detecting, from the plurality of digital images, Gaussian brightness falloff patterns indicative of the fingers of the hand that are visible;
identifying a centerline axis of the visible fingers of the hand based on the detected Gaussian brightness falloff patterns indicative of the fingers without identifying edges of the visible fingers; and
identifying the pixels that correspond to the visible fingers based on the identified centerline axis of the visible fingers;
tracking motion of the identified pixels that correspond to the visible fingers through the plurality of digital images; and
constructing a model of the visible fingers based on the identified pixels that correspond to the visible fingers and the tracked motion of the identified pixels that correspond to the visible fingers.
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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.
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Citations
19 Claims
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1. A method identifying a hand by analyzing captured images, the method comprising:
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activating at least one light source to illuminate a field of view containing a background and the hand including fingers; operating a camera to capture a plurality of digital images including a first digital image captured at a time when the at least one light source is illuminating the field of view; identifying pixels of the plurality of digital images that correspond to fingers of the hand that are visible in the plurality of digital images rather than to the background, the identifying including; detecting, from the plurality of digital images, Gaussian brightness falloff patterns indicative of the fingers of the hand that are visible; identifying a centerline axis of the visible fingers of the hand based on the detected Gaussian brightness falloff patterns indicative of the fingers without identifying edges of the visible fingers; and identifying the pixels that correspond to the visible fingers based on the identified centerline axis of the visible fingers; tracking motion of the identified pixels that correspond to the visible fingers through the plurality of digital images; and constructing a model of the visible fingers based on the identified pixels that correspond to the visible fingers and the tracked motion of the identified pixels that correspond to the visible fingers. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. An image capture and analysis system for identifying a hand by analyzing captured images, the image capture and analysis system comprising:
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at least one camera oriented toward a field of view containing a background and the 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 an image analyzer 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; operate the at least one camera to capture a plurality of digital images including a first digital image captured at a time when the at least one light source is illuminating the field of view; identify pixels of the plurality of digital images that correspond to fingers of the hand that are visible in the plurality of digital images rather than to the background, the image analyzer identifying the pixels by; detecting, from the plurality of digital images, Gaussian brightness falloff patterns indicative of the fingers of the hand that are visible; identifying a centerline axis of the visible fingers of the hand based on the detected Gaussian brightness falloff patterns indicative of the fingers without identifying edges of the visible fingers; and identifying the pixels that correspond to the visible fingers based on the identified centerline axis of the visible fingers; and track motion of the identified pixels that correspond to the visible fingers through the plurality of digital images; and construct a model of the visible fingers based on the identified pixels that correspond to the visible fingers and the tracked motion of the identified pixels that correspond to the visible fingers. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. A wearable goggle, comprising:
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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; operate the at least one camera to capture a plurality of digital images including a first digital image captured at a time when the at least one light source is illuminating the field of view; identify pixels of the plurality of digital images that correspond to fingers of the hand that are visible in the plurality of digital images rather than to the background, the processor identifying the pixels by; detecting, from the plurality of digital images, Gaussian brightness falloff patterns indicative of the fingers of the hand that are visible; identifying a centerline axis of the visible fingers of the hand based on the detected Gaussian brightness falloff patterns indicative of the fingers without identifying edges of the visible fingers; and identifying the pixels that correspond to the visible fingers based on the identified centerline axis of the visible fingers; and track motion of the identified pixels that correspond to the visible fingers through the plurality of digital images; and construct a model of the visible fingers based on the identified pixels that correspond to the visible fingers and the tracked motion of the identified pixels that correspond to the visible fingers.
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Specification