Depth masks for image segmentation for depth-based computational photography
First Claim
1. A method of depth-based computational photography comprising:
- recording a first image using a stereoscopic camera system;
establishing a disparity map, via a processor executing codes instructions, of the first image including a determination of pixel distance between features in the first image and the features in a second image;
identifying holes in disparity map of the first image and computationally shrinking at least one hole in the disparity map via applying a weighted average of radially sampled disparity map values proximate to the at least one hole, wherein sampled disparity map values for pixels closer to the at least one hole have greater weighting than sampled disparity map values for pixels further from the at least one hole;
removing noise in the disparity map via edge smoothing;
determining pixel depth values from the disparity map; and
encoding the pixel depth values into a depth mask for a composite plural image.
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Abstract
A depth-based computational photography method includes recording a first image using a stereoscopic camera system, establishing a disparity map, via a processor, of the first image including a determination of pixel distance between features in the first image and the features in a second image, determining a histogram of pixel disparity values from the disparity map, and removing statistical outlier pixel disparity values. The method further includes identifying holes in disparity map of the first image and computationally shrinking holes in the disparity map via averaging disparity map values based on radially sampled areas proximate to the hole and sharpening histogram pixel disparity value peaks by shifting pixel disparity values in a close neighborhood range of a histogram pixel disparity value peak maximum closer to a pixel disparity value at the histogram pixel disparity value peak maximum.
54 Citations
20 Claims
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1. A method of depth-based computational photography comprising:
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recording a first image using a stereoscopic camera system; establishing a disparity map, via a processor executing codes instructions, of the first image including a determination of pixel distance between features in the first image and the features in a second image; identifying holes in disparity map of the first image and computationally shrinking at least one hole in the disparity map via applying a weighted average of radially sampled disparity map values proximate to the at least one hole, wherein sampled disparity map values for pixels closer to the at least one hole have greater weighting than sampled disparity map values for pixels further from the at least one hole; removing noise in the disparity map via edge smoothing; determining pixel depth values from the disparity map; and encoding the pixel depth values into a depth mask for a composite plural image. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. An information handling system comprising:
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a stereoscopic camera system for recording a first image; a processor operatively coupled to the stereoscopic camera system to establish a disparity map associated with the first image including a determination of pixel distance between features in the first image and the features in a second image; the processor to execute instructions to identify holes in the disparity map associated with the first image and process the disparity map by computationally shrinking the holes using scan conversion applied to the disparity map with weighted, averaged disparity map values radially sampled from areas proximate to the hole, where disparity map values of pixels closer to the holes have a greater weighting value than disparity map values of pixels further from the holes in the weighted averaging; the processor to encode the disparity map into a depth mask of a composite plural image; and a memory operatively coupled to the processor, the memory for storing the composite plural image with the depth mask. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A method of depth-based computational photography comprising:
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recording a first image using a stereoscopic camera system; establishing a disparity map, via a processor executing code instructions, of the first image including a determination of pixel distance between features in the first image and the features in a second image; determining a histogram of pixel disparity values from the disparity map;
removing statistical outlier pixel disparity values;identifying holes in disparity map of the first image and computationally shrinking holes in the disparity map via averaging disparity map values proximate to the hole; determining whether any scanned disparity map values are different in value to those proximate to the hole; rejecting scanned pixel disparity map values with different value to those proximate to the hole and determining a weighted average based on radially sampled areas of remaining scanned disparity map values proximate to the hole; and sharpening histogram pixel disparity value peaks by shifting pixel disparity values in a close neighborhood range of a histogram pixel disparity value peak maximum closer to a pixel disparity value at the histogram pixel disparity value peak maximum for a composite plural image of the first and second images. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification