Systems and methods for measuring depth based upon occlusion patterns in images

US9129377B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9129377-B2
Application numberUS-201414526407-A
CountryUS
Kind codeB2
Filing dateOct 28, 2014
Priority dateAug 21, 2012
Publication dateSep 8, 2015
Grant dateSep 8, 2015

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Abstract

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Systems in accordance with embodiments of the invention can perform parallax detection and correction in images captured using array cameras. Due to the different viewpoints of the cameras, parallax results in variations in the position of objects within the captured images of the scene. Methods in accordance with embodiments of the invention provide an accurate account of the pixel disparity due to parallax between the different cameras in the array, so that appropriate scene-dependent geometric shifts can be applied to the pixels of the captured images when performing super-resolution processing. In a number of embodiments, generating depth estimates considers the similarity of pixels in multiple spectral channels. In certain embodiments, generating depth estimates involves generating a confidence map indicating the reliability of depth estimates.

First claim

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What is claimed is: 1. A camera array, comprising: a plurality of cameras configured to capture images of a scene from different viewpoints in complementary occlusion zones around a reference viewpoint; a processor; and memory containing an image processing application; wherein the image processing application stored in memory directs the processor to: separately configure imaging parameters for each of the plurality of cameras; read out image data from the plurality of cameras including a set of images captured from different viewpoints; store the image data in the memory; normalize the set of images to increase the similarity of corresponding pixels within the set of images; determine initial depth estimates for pixel locations in an image from the reference viewpoint based upon the disparity at which corresponding pixels in the set of images have the highest degree of similarity; compare the similarity of the corresponding pixels in the set of images to detect mismatched pixels; when an initial depth estimate does not result in the detection of a mismatch between corresponding pixels in the set of images, selecting the initial depth estimate as the depth estimate for the pixel location in the image from the reference viewpoint; and when an initial depth estimate results in the detection of a mismatch between corresponding pixels in the set of images, updating the depth estimate for the pixel location in the image from the reference viewpoint by: determining a set of candidate depth estimates using a plurality of competing subsets of the set of images based upon disparities at which corresponding pixels in each of the plurality of competing subsets of images have the highest degree of similarity, where the competing subsets correspond to patterns of visibility within the scene; and selecting the candidate depth of the subset having the corresponding pixels with the highest degree of similarity as the updated depth estimate for the pixel location in the image from the reference viewpoint. 2. The camera array of claim 1 , wherein the plurality of cameras comprises different types of cameras that capture different wavelengths of light. 3. The camera array of claim 2 , wherein at least one camera of each different type is located in each quadrant surrounding the reference viewpoint. 4. The camera array of claim 3 , wherein each of the two red color cameras is located at a corner location of the 3×3 array of cameras, and wherein each of the two blue color cameras is located at a corner location of the 3×3 array of cameras. 5. The camera array of claim 3 , wherein the image processing application further directs the processor to select the viewpoint of the reference camera as the reference viewpoint. 6. The camera array of claim 2 , wherein the plurality of cameras includes at least a 3×3 array of cameras comprising: a reference camera at the center of the 3×3 array of cameras; two red color cameras in complementary occlusion zones located on opposite sides of the 3×3 array of cameras; two blue color cameras located in complementary occlusion zones on opposite sides of the 3×3 array of cameras; and four green color cameras in complementary occlusion zones surrounding the reference camera. 7. The camera array of claim 6 , wherein: each of the four green color cameras surrounding the reference camera is disposed at a corner location of the 3×3 array of cameras; and each competing subsets of images only includes one of the images captured by the four green color cameras. 8. The camera array of claim 6 , wherein the reference camera is a green color camera. 9. The camera array of claim 6 , wherein the reference camera is one of: a camera that incorporates a Bayer filter, a camera that is configured to capture infrared light, and a camera that is configured to capture ultraviolet light. 10. The camera array of claim 2 , wherein: the plurality of cameras captures images in a plurality of color channels; and the image processing application further directs the processor to determine an initial depth estimate for a given pixel location in an image from the reference viewpoint based upon the disparity at which corresponding pixels in the set of images have the highest degree of similarity by: identifying pixels in at least a subset of the set of images that correspond to the given pixel location in the image from the reference viewpoint based upon expected disparity at a plurality of depths; in each of a plurality of color channels, comparing the similarity of the pixels that are identified as corresponding in the selected color channel at each of the plurality of depths; and selecting the depth from the plurality of depths at which the identified corresponding pixels in each of the plurality of color channels have the highest degree of similarity as a depth estimate for the given pixel location in the image from the reference viewpoint. 11. The camera array of claim 1 , wherein the same number of images are in each of the competing subsets of images. 12. The camera array of claim 11 , wherein: the plurality of cameras captures images in a plurality of color channels; and each competing subset of images includes the same number of images from at least one of the plurality of color channels. 13. The camera array of claim 12 , wherein each competing subset of images includes at least one image from each of the plurality of color channels. 14. The camera array of claim 12 , wherein each competing subset of images includes at least one image from all but one of the plurality of color channels. 15. The camera array of claim 1 , wherein the image processing application stored in memory directs the processor to record in at least one visibility map that the pixel location in the image from the reference viewpoint is visible in each image in the subset of images used to determine the updated depth estimate for the pixel location. 16. The camera array of claim 15 , wherein the image processing application stored in memory directs the processor to record in the at least one visibility map the visibility of the pixel location in the image from the reference viewpoint in a given image that is not part of the subset of images used to determine the updated depth estimate for the pixel location based upon the degree of similarity of the corresponding pixel in the given image to the corresponding pixels in the subset of images used to determine the updated depth estimate for the pixel location. 17. The camera array of claim 15 , wherein the optics within each camera are configured so that the pixels of the camera sample the same object space with sub-pixel offsets. 18. The camera array of claim 17 , wherein the image processing application further directs the processor to: fuse pixels from the set of images using the depth estimates to create a fused image having a resolution that is greater than the resolutions of the images in the set of images by: identifying the pixels from the set of images that are visible in an image from the reference viewpoint using the at least one visibility map; and applying scene dependent geometric shifts to the pixels from the set of images that are visible in an image from the reference viewpoint to shift the pixels into the reference viewpoint, where the scene dependent geometric shifts are determined using the depth estimates; and fusing the shifted pixels from the set of images to create a fused image from the reference viewpoint having a resolution that is greater than the resolutions of the images in the set

Assignees

Inventors

Classifications

  • Optical arrangements associated therewith, e.g. for beam-splitting or for colour correction · CPC title

  • Adjusting depth or disparity · CPC title

  • with means for altering, e.g. increasing, the depth of field or depth of focus · CPC title

  • using fly-eye lenses, e.g. arrangements of circular lenses · CPC title

  • Synthesising a monoscopic image signal from stereoscopic images, e.g. synthesising a panoramic or high resolution monoscopic image · CPC title

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What does patent US9129377B2 cover?
Systems in accordance with embodiments of the invention can perform parallax detection and correction in images captured using array cameras. Due to the different viewpoints of the cameras, parallax results in variations in the position of objects within the captured images of the scene. Methods in accordance with embodiments of the invention provide an accurate account of the pixel disparity d…
Who is the assignee on this patent?
Pelican Imaging Corp
What technology area does this patent fall under?
Primary CPC classification G02B27/0075. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Sep 08 2015 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 12 related publications on this page (citations in our corpus or others sharing the same primary CPC).