Visual language for human computer interfaces
First Claim
1. A computer-implemented method for recognizing hand gestures, the method comprising:
- performing an adaptive hand detection, performing the adaptive hand detection comprising;
presenting a region of interest (ROI) on a display,receiving a digital color image of a user hand against a background, the digital color image captured using a 2-D digital image capturing device, the digital color image being represented by pixels in a first color space,selecting a set of pixels of the digital color image in the first color space from the pixels of the digital color image within the ROI, the selected set of pixels of the digital color image in the first color space describing a general parametric model associated with the digital color image in the first color space,obtaining specific parametric templates in additional color spaces, each specific parametric template comprising a selected set of pixels in the ROI representing the user hand in a corresponding color space of the additional color spaces, the additional color spaces emphasizing chrominance over luminance information, andobtaining an updated specific parametric template by combining the specific parametric templates in the additional color spaces;
obtaining a contour of the user hand by applying the updated specific parametric template to subsequent digital images of the user hand, obtaining the contour of the user hand comprising;
identifying points corresponding to fingertips, points between fingers, and convex hulls generated by the fingertips in the subsequent digital images based on the updated specific parametric template, andgenerating a polygonal contour map of the user hand based on the points; and
detecting a hand gesture based on the contour of the user hand, detecting the hand gesture comprising analyzing a structure, orientation and motion of the user hand based on the polygonal contour map through a nonlinear classifier to select the hand gesture from a pre-defined vocabulary of gestures.
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Abstract
Embodiments of the invention recognize human visual gestures, as captured by image and video sensors, to develop a visual language for a variety of human computer interfaces. One embodiment provides a method for recognizing a hand gesture positioned by a user hand. The method includes steps of capturing a digital color image of a user hand against a background, applying a general parametric model to the digital color image of the user hand to generate a specific parametric template of the user hand, receiving a second digital image of the user hand positioned to represent a hand gesture, detecting a hand contour of the hand gesture based at least in part on the specific parametric template of the user hand, and recognizing the hand gesture based at least in part on the detected hand contour. Other embodiments include recognizing hand gestures, facial gestures or body gestures captured in a video.
57 Citations
45 Claims
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1. A computer-implemented method for recognizing hand gestures, the method comprising:
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performing an adaptive hand detection, performing the adaptive hand detection comprising; presenting a region of interest (ROI) on a display, receiving a digital color image of a user hand against a background, the digital color image captured using a 2-D digital image capturing device, the digital color image being represented by pixels in a first color space, selecting a set of pixels of the digital color image in the first color space from the pixels of the digital color image within the ROI, the selected set of pixels of the digital color image in the first color space describing a general parametric model associated with the digital color image in the first color space, obtaining specific parametric templates in additional color spaces, each specific parametric template comprising a selected set of pixels in the ROI representing the user hand in a corresponding color space of the additional color spaces, the additional color spaces emphasizing chrominance over luminance information, and obtaining an updated specific parametric template by combining the specific parametric templates in the additional color spaces; obtaining a contour of the user hand by applying the updated specific parametric template to subsequent digital images of the user hand, obtaining the contour of the user hand comprising; identifying points corresponding to fingertips, points between fingers, and convex hulls generated by the fingertips in the subsequent digital images based on the updated specific parametric template, and generating a polygonal contour map of the user hand based on the points; and detecting a hand gesture based on the contour of the user hand, detecting the hand gesture comprising analyzing a structure, orientation and motion of the user hand based on the polygonal contour map through a nonlinear classifier to select the hand gesture from a pre-defined vocabulary of gestures. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A computer-implemented method for recognizing hand gestures, the method comprising:
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performing an adaptive hand detection, performing the adaptive hand detection comprising; presenting a region of interest (ROI) on a display, capturing an input video of a user hand against a background, the input video comprising a plurality of video frames of the user hand captured using a 2-D digital image capturing device, and a video frame of the plurality video frame representing a digital color image of the user hand at a time instance, the digital color image being represented by pixels in a first color space, selecting a video frame of the plurality of the video frames of the input video as a reference frame, selecting a set of pixels of the reference frame in the first color space from the pixels of the reference frame within the ROI, the selected set of pixels of the reference frame in the first color space describing a general parametric model associated with the reference frame in the first color space, obtaining specific parametric templates in additional color spaces, each specific parametric template comprising a selected set of pixels in the ROI representing the user hand in a corresponding color space of the additional color spaces, the additional color spaces emphasizing chrominance over luminance information, and obtaining an updated specific parametric template by combining the specific parametric templates in the additional color spaces; subsequently receiving one or more video frames of the input video of the user hand, wherein the user hand in a subsequently received video frame is positioned to represent a hand gesture; obtaining contours of the user hand in the subsequent video frames by applying the updated specific parametric template to the subsequent video frames of the user hand, obtaining a contour of the user hand in a video frame comprising; identifying points corresponding to fingertips, points between fingers, and convex hulls generated by the fingertips in the subsequent digital images based on the updated specific parametric template, and generating a polygonal contour map of the user hand based on the points, obtaining motion vectors of features of the user hand in the subsequent video frames based on the updated specific parametric template; and detecting a hand gesture based on the contour of the user hand and the motion vectors, detecting the hand gesture comprising analyzing a structure, orientation and motion of the user hand based on the polygonal contour map through a nonlinear classifier to select the hand gesture from a pre-defined vocabulary of gestures. - View Dependent Claims (14)
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15. A computer-implemented method for recognizing hand gestures, the method comprising:
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performing an adaptive hand detection, performing the adaptive hand detection comprising; presenting a region of interest (ROI) on a display, receiving a digital color image of a user hand against a background, the digital color image captured using a 2-D digital image capturing device, the digital color image being represented by pixels in a first color space, obtaining specific parametric templates in additional color spaces, each specific parametric template comprising a selected set of pixels in the ROI representing the user hand in a corresponding color space of the additional color spaces, the additional color spaces emphasizing chrominance over luminance information, and obtaining an updated specific parametric template by combining the specific parametric templates in the additional color spaces; obtaining a contour of the user hand by applying the updated specific parametric template to subsequent digital images of the user hand, obtaining the contour of the user hand comprising; detecting pixels of the set of pixels that represent noise, regrouping a plurality of isolated regions of the digital color image into one or more segments based on the updated specific parametric template, selecting a largest segment of the one or more segments to represent the contour of the user hand, identifying points corresponding to fingertips, points between fingers, and convex hulls generated by the fingertips in the subsequent digital images based on the updated specific parametric template, and generating a polygonal contour map of the user hand based on the points; and detecting a hand gesture based on the contour of the user hand, detecting the hand gesture comprising analyzing a structure, orientation and motion of the user hand based on the polygonal contour map through a nonlinear classifier to select the hand gesture from a pre-defined vocabulary of gestures.
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16. A non-transitory computer-readable storage medium storing executable computer program instructions for recognizing hand gestures, the computer programs instructions comprising code for:
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performing an adaptive hand detection, performing the adaptive hand detection comprising; presenting a region of interest (ROI) on a display, receiving a digital color image of a user hand against a background, the digital color image captured using a 2-D digital image capturing device, the digital color image being represented by pixels in a first color space, selecting a set of pixels of the digital color image in the first color space from the pixels of the digital color image within the ROI, the selected set of pixels of the digital color image in the first color space describing a general parametric model associated with the digital color image in the first color space, obtaining specific parametric templates in additional color spaces, each specific parametric template comprising a selected set of pixels in the ROI representing the user hand in a corresponding color space of the additional color spaces, the additional color spaces emphasizing chrominance over luminance information, and obtaining an updated specific parametric template by combining the specific parametric templates in the additional color spaces; obtaining a contour of the user hand by applying the updated specific parametric template to subsequent digital images of the user hand, obtaining the contour of the user hand comprising; identifying points corresponding to fingertips, points between fingers, and convex hulls generated by the fingertips in the subsequent digital images based on the updated specific parametric template, and generating a polygonal contour map of the user hand based on the points; and detecting a hand gesture based on the contour of the user hand, detecting the hand gesture comprising analyzing a structure, orientation and motion of the user hand based on the polygonal contour map through a nonlinear classifier to select the hand gesture from a pre-defined vocabulary of gestures. - View Dependent Claims (17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27)
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28. A non-transitory computer-readable storage medium storing executable computer program instructions for recognizing hand gestures, the computer program instructions comprising code for:
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performing an adaptive hand detection, performing the adaptive hand detection comprising; presenting a region of interest (ROI) on a display, capturing an input video of a user hand against a background, the input video comprising a plurality of video frames of the user hand captured using a 2-D digital image capturing device, and a video frame of the plurality video frame representing a digital color image of the user hand at a time instance, the digital color image being represented by pixels in a first color space, selecting a video frame of the plurality of the video frames of the input video as a reference frame, selecting a set of pixels of the reference frame in the first color space from the pixels of the reference frame within the ROI, the selected set of pixels of the reference frame in the first color space describing a general parametric model associated with the reference frame in the first color space, obtaining specific parametric templates in additional color spaces, each specific parametric template comprising a selected set of pixels in the ROI representing the user hand in a corresponding color space of the additional color spaces, the additional color spaces emphasizing chrominance over luminance information, and obtaining an updated specific parametric template by combining the specific parametric templates in the additional color spaces; subsequently receiving one or more video frames of input video of the user hand, wherein the user hand in a subsequently received video frame is positioned to represent a hand gesture; obtaining contours of the user hand in the subsequent video frames by applying the updated specific parametric template to the subsequent video frames of the user hand, obtaining a contour of the user hand in a video frame comprising; identifying points corresponding to fingertips, points between fingers, and convex hulls generated by the fingertips in the subsequent digital images based on the updated specific parametric template, and generating a polygonal contour map of the user hand based on the points; obtaining motion vectors features of the user hand in the subsequent video frames based on the updated specific parametric template; and detecting a hand gesture based on the contour of the user hand and the motion vectors, detecting the hand gesture comprising analyzing a structure, orientation and motion of the user hand based on the polygonal contour map through a nonlinear classifier to select the hand gesture from a pre-defined vocabulary of gestures. - View Dependent Claims (29)
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30. A non-transitory computer-readable storage medium storing executable computer program instructions for recognizing hand gestures, the computer program instructions comprising code for:
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performing an adaptive hand detection, performing the adaptive hand detection comprising; presenting a region of interest (ROI) on a display, receiving a digital color image of a user hand against a background, the digital color image captured using a 2-D digital image capturing device, the digital color image being represented by pixels in a first color space, obtaining specific parametric templates in additional color spaces, each specific parametric template comprising a selected set of pixels in the ROI representing the user hand in a corresponding color space of the additional color spaces, the additional color spaces emphasizing chrominance over luminance information, and obtaining an updated specific parametric template by combining the specific parametric templates in the additional color spaces; obtaining a contour of the user hand by applying the updated specific parametric template to subsequent digital images of the user hand, obtaining the contour of the user hand comprising; detecting pixels of the set of pixels that represent noise, regrouping a plurality of isolated regions of the digital color image into one or more segments based on the updated specific parametric template, selecting a largest segment of the one or more segments to represent the contour of the user hand, identifying points corresponding to fingertips, points between fingers, and convex hulls generated by the fingertips in the subsequent digital images based on the updated specific parametric template, and generating a polygonal contour map of the user hand based on the points; and detecting a hand gesture based on the contour of the user hand, detecting the hand gesture comprising analyzing a structure, orientation and motion of the user hand based on the polygonal contour map through a nonlinear classifier to select the hand gesture from a pre-defined vocabulary of gestures.
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31. An apparatus for recognizing hand gestures, the apparatus comprising:
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a computer processor for performing steps comprising; performing an adaptive hand detection, performing the adaptive hand detection comprising; presenting a region of interest (ROI) on a display, receiving a digital color image of a user hand against a background, the digital color image captured using a 2-D digital image capturing device, the digital color image being represented by pixels in a first color space, selecting a set of pixels of the digital color image in the first color space from the pixels of the digital color image within the ROI, the selected set of pixels of the digital color image in the first color space describing a general parametric model associated with the digital color image in the first color space, obtaining specific parametric templates in additional color spaces, each specific parametric template comprising a selected set of pixels in the ROI representing the user hand in a corresponding color space of the additional color spaces, the additional color spaces emphasizing chrominance over luminance information, and obtaining an updated specific parametric template by combining the specific parametric templates in the additional color spaces; obtaining a contour of the user hand by applying the updated specific parametric template to subsequent digital images of the user hand, obtaining the contour of the user hand comprising; identifying points corresponding to fingertips, points between fingers, and convex hulls generated by the fingertips in the subsequent digital images based on the updated specific parametric template, and generating a polygonal contour map of the user hand based on the points; and detecting a hand gesture based on the contour of the user hand, detecting the hand gesture comprising analyzing a structure, orientation and motion of the user hand based on the polygonal contour map through a nonlinear classifier to select the hand gesture from a pre-defined vocabulary of gestures. - View Dependent Claims (32, 33, 34, 35, 36, 37, 38, 39, 40, 41)
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42. An apparatus for recognizing hand gestures, the apparatus comprising:
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a computer processor for performing steps comprising; performing an adaptive hand detection, performing the adaptive hand detection comprising; presenting a region of interest (ROI) on a display, capturing an input video of a user hand against a background, the input video comprising a plurality of video frames of the user hand captured using a 2-D digital image capturing device, and a video frame of the plurality video frame representing a digital color image of the user hand at a time instance, the digital color image being represented in pixels in a first color space, selecting a video frame of the plurality of the video frames of the input video as a reference frame, selecting a set of pixels of the reference frame in the first color space from the pixels of the reference frame within the ROI, the selected set of pixels of the reference frame in the first color space describing a general parametric model associated with the reference frame in the first color space, obtaining specific parametric templates in additional color spaces, each specific parametric template comprising a selected set of pixels in the ROI representing the user hand in a corresponding color space of the additional color spaces, the additional color spaces emphasizing chrominance over luminance information, and obtaining an updated specific parametric template by combining the specific parametric templates in the additional color spaces; subsequently receiving one or more video frames of the input video of the user hand, wherein the user hand in a subsequently received video frame is positioned to represent a hand gesture; obtaining contours of the user hand in the subsequent video frames by applying the updated specific parametric template to the subsequent video frames of the user hand, obtaining a contour of the user hand in a video frame comprising; identifying points corresponding to fingertips, points between fingers, and convex hulls generated by the fingertips in the subsequent digital images based on the updated specific parametric template, and generating a polygonal contour map of the user hand based on the points; obtaining motion vectors of features of the user hand in the subsequent video frames based on the updated specific parametric template; and detecting a hand gesture based on the contour of the user hand and the motion vectors, detecting the hand gesture comprising analyzing a structure, orientation and motion of the user hand based on the polygonal contour map through a nonlinear classifier to select the hand gesture from a pre-defined vocabulary of gestures. - View Dependent Claims (43)
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44. A computer-implemented method for recognizing human visual gestures positioned by a portion of a human body, the method comprising:
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performing an adaptive detection of the portion of the human body, performing the adaptive detection comprising; presenting a region of interest (ROI) on a display, receiving a digital color image of the portion of the human body against a background, the digital color image captured using a 2-D digital image capturing device, the digital color image being represented by pixels in a first color space, selecting a set of pixels of the digital color image in the first color space from the pixels of the digital color image within the ROI, the selected set of pixels of the digital color image in the first color space describing a general parametric model associated with the digital color image in the first color space, obtaining specific parametric templates in additional color spaces, each specific parametric template comprising a selected set of pixels in the ROI representing the portion of the human body in a corresponding color space of the additional color spaces, the additional color spaces emphasizing chrominance over luminance information, and obtaining an updated specific parametric template by combining the specific parametric templates in the additional color spaces; obtaining a contour of the portion of the human body by applying the updated specific parametric template to subsequent digital images of the portion of the human body, obtaining the contour of the portion of the human body comprising; identifying points corresponding to fingertips, points between fingers, and convex hulls generated by the fingertips in the subsequent digital images based on the updated specific parametric template, and generating a polygonal contour map of the portion of the human body based on the points; and detecting a human visual gesture based on the contour, detecting the human visual gesture comprising analyzing a structure, orientation and motion of the portion of the human body based on the polygonal contour map through a nonlinear classifier to select the human visual gesture from a pre-defined vocabulary of gestures. - View Dependent Claims (45)
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Specification