Scene enhancements in off-center peripheral regions for nonlinear lens geometries
First Claim
1. Within an image acquisition system comprising a non-linear, wide-angled lens and an imaging sensor, a method of enhancing a scene containing one or more off-center peripheral regions, the method comprising:
- acquiring, using a nonlinear, wide-angled lens and an imaging sensor, an initial distorted image with a large field of view;
generating a reconstructed image from the initial distorted image, wherein the reconstructed image includes a plurality of reconstructed regions;
wherein each reconstructed region of the plurality of reconstructed regions has a corresponding region quality;
wherein the region quality of each reconstructed region of the plurality of reconstructed regions is based on reconstruction factors of reconstructed pixels within the reconstructed region;
wherein the reconstruction factor for a reconstructed pixel reflects how much data, from the image sensor, the reconstructed pixel was extrapolated based on;
based on the region qualities of said plurality of reconstructed regions, determining one or more reduced quality regions within said plurality of reconstructed regions;
determining whether any undetected faces below a size threshold are likely to exist in the one or more reduced quality regions; and
in response to determining that any undetected faces below the size threshold are likely to exist in the one or more reduced quality regions, performing the steps of;
generating one or more enhanced regions of interest that correspond to the one or more reduced quality regions; and
applying face detecting or tracking, or both, to the one or more enhanced regions of interest to confirm presence of a face below the size threshold.
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Accused Products
Abstract
A technique of enhancing a scene containing one or more off-center peripheral regions within an initial distorted image captured with a large field of view includes determining and extracting an off-center region of interest (hereinafter “ROI”) within the image. Geometric correction is applied to reconstruct the off-center ROI into a rectangular frame of reference as a reconstructed ROI. A quality of reconstructed pixels is determined within the reconstructed ROI. Image analysis is selectively applied to the reconstructed ROI based on the quality of the reconstructed pixels.
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Citations
18 Claims
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1. Within an image acquisition system comprising a non-linear, wide-angled lens and an imaging sensor, a method of enhancing a scene containing one or more off-center peripheral regions, the method comprising:
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acquiring, using a nonlinear, wide-angled lens and an imaging sensor, an initial distorted image with a large field of view; generating a reconstructed image from the initial distorted image, wherein the reconstructed image includes a plurality of reconstructed regions; wherein each reconstructed region of the plurality of reconstructed regions has a corresponding region quality; wherein the region quality of each reconstructed region of the plurality of reconstructed regions is based on reconstruction factors of reconstructed pixels within the reconstructed region; wherein the reconstruction factor for a reconstructed pixel reflects how much data, from the image sensor, the reconstructed pixel was extrapolated based on; based on the region qualities of said plurality of reconstructed regions, determining one or more reduced quality regions within said plurality of reconstructed regions; determining whether any undetected faces below a size threshold are likely to exist in the one or more reduced quality regions; and in response to determining that any undetected faces below the size threshold are likely to exist in the one or more reduced quality regions, performing the steps of; generating one or more enhanced regions of interest that correspond to the one or more reduced quality regions; and applying face detecting or tracking, or both, to the one or more enhanced regions of interest to confirm presence of a face below the size threshold. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A digital image acquisition device, comprising:
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a non-linear, wide-angled lens and an imaging sensor configured to capture digital images of scenes containing one or more off-center peripheral regions, including an initial distorted image with a large field of view; a processor; a memory having code embedded therein for programming the processor to perform a method of enhancing a scene containing one or more off-center peripheral regions, wherein the method comprises; generating a reconstructed image from the initial distorted image, wherein the reconstructed image includes a plurality of reconstructed regions; wherein each reconstructed region of the plurality of reconstructed regions has a corresponding region quality; wherein the region quality of each reconstructed region of the plurality of reconstructed regions is based on reconstruction factors of reconstructed pixels within the reconstructed region; wherein the reconstruction factor for a reconstructed pixel reflects how much data, from the image sensor, the reconstructed pixel was extrapolated based on; based on the region qualities of said plurality of reconstructed regions, determining one or more reduced quality regions within said plurality of reconstructed regions; determining whether any undetected faces below a size threshold are likely to exist in the one or more reduced quality regions; and in response to determining that any undetected faces below the size threshold are likely to exist in the one or more reduced quality regions, performing the steps of; generating one or more enhanced regions of interest that correspond to the one or more reduced quality regions; and applying face detecting or tracking, or both, to the one or more enhanced regions of interest to confirm presence of a face below the size threshold. - View Dependent Claims (8, 9, 10, 11, 12)
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13. One or more non-transitory, processor-readable storage media having code embedded therein for programming a processor to perform a method of enhancing a scene captured with a non-linear, wide-angled lens and containing one or more off-center peripheral regions, wherein the method comprises:
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acquiring using a nonlinear, wide-angled lens and an imaging sensor, an initial distorted image with a large field of view; generating a reconstructed image from the initial distorted image, wherein the reconstructed image includes a plurality of reconstructed regions; wherein each reconstructed region of the plurality of reconstructed regions has a corresponding region quality; wherein the region quality of each reconstructed region of the plurality of reconstructed regions is based on reconstruction factors of reconstructed pixels within the reconstructed region; wherein the reconstruction factor for a reconstructed pixel reflects how much data, from the image sensor, the reconstructed pixel was extrapolated based on; based on the region qualities of said plurality of reconstructed regions, determining one or more reduced quality regions within said plurality of reconstructed regions; determining whether any undetected faces below a size threshold are likely to exist in the one or more reduced quality regions; and in response to determining that any undetected faces below the size threshold are likely to exist in the one or more reduced quality regions, performing the steps of; generating one or more enhanced regions of interest that correspond to the one or more reduced quality regions; and applying face detecting or tracking, or both, to the one or more enhanced regions of interest to confirm presence of a face below the size threshold. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification