Video image quality
First Claim
1. One or more processor-accessible media comprising processor-executable instructions that, when executed, direct a device to perform actions comprising:
- selecting training pixels from an image frame based on a defined skin color range;
building a skin-color model using the selected training pixels;
detecting a skin portion of the image frame using the skin-color model; and
adjusting the image frame with regard to the detected skin portion.
2 Assignments
0 Petitions
Accused Products
Abstract
Video image quality may be improved by correcting exposure levels and/or enhancing contrast amounts on each frame. One or more of the following phases may be implemented: skin-color model building, face detecting, exposure level correcting, and contrast enhancing. In a described implementation, a Gaussian skin-color model is built for each image frame during runtime. The Gaussian skin-color model is built with training pixels that are selected responsive to a defined skin color range, which is created offline from manually-selected skin pixels of multiple test sequences. In another described implementation, each pixel of an image frame is re-exposed using a ratio of contrast amount control variables (CACVs). More specifically, a pixel may be converted to a corresponding light intensity using a first CACV, and the corresponding light intensity may be reconverted to a pixel using a second CACV to enhance the contrast and possibly reduce fuzziness of the image frame.
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Citations
39 Claims
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1. One or more processor-accessible media comprising processor-executable instructions that, when executed, direct a device to perform actions comprising:
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selecting training pixels from an image frame based on a defined skin color range;
building a skin-color model using the selected training pixels;
detecting a skin portion of the image frame using the skin-color model; and
adjusting the image frame with regard to the detected skin portion. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A device comprising:
a skin-color model builder that is capable of accepting a defined skin color range and an image frame as input, the skin-color model builder adapted to select training pixels from the image frame based on the defined skin color range and to build a skin-color model at runtime for the image frame using the selected training pixels. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. An arrangement for video image processing in conjunction with skin color modeling, the arrangement comprising:
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selection means for selecting training pixels from an image frame using a predefined skin color range; and
build means for building a skin-color model using the selected training pixels. - View Dependent Claims (23, 24, 25, 26, 27, 28)
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29. A device that is configured to perform actions comprising:
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building a skin-color model for an image frame using a defined skin color range;
detecting a facial portion in the image frame using the skin-color model; and
correcting an exposure level of the image frame based on a luminance value of the detected facial portion. - View Dependent Claims (30, 31, 32, 33, 34, 35, 36, 37, 38)
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39. A runtime method comprising:
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selecting training pixels from an image frame based on a predefined skin color range, the predefined skin color range created offline;
building a Gaussian skin-color model using the selected training pixels;
detecting a facial portion of the image frame using the Gaussian skin-color model and a skin pixel probability threshold; and
correcting an exposure level of the image frame with regard to the detected facial portion.
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Specification