The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 13, 2024

Filed:

Oct. 28, 2022
Applicant:

Owl Autonomous Imaging, Inc., Fairport, NY (US);

Inventors:

Srinath Obla, Rochester, NY (US);

Eugene M. Petilli, Victor, NY (US);

Akash Chintha, Rochester, NY (US);

Charles F. Gershman, Pleasanton, CA (US);

Francis J. Cusack, Jr., Wilmington, NC (US);

Assignee:

Owl Autonomous Imaging, Inc., Fairport, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04N 13/243 (2018.01); G06T 7/593 (2017.01); H04N 13/178 (2018.01); H04N 13/25 (2018.01); H04N 13/296 (2018.01); H04N 23/957 (2023.01); H04N 13/00 (2018.01);
U.S. Cl.
CPC ...
H04N 13/243 (2018.05); G06T 7/593 (2017.01); H04N 13/178 (2018.05); H04N 13/25 (2018.05); H04N 13/296 (2018.05); H04N 23/957 (2023.01); G06T 2207/10012 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); H04N 2013/0081 (2013.01);
Abstract

Embodiments of systems and methods for multi-aperture ranging are disclosed. An embodiment of an image processing system includes at least one processor and memory configured to receive a multi-aperture image set that includes a high-resolution subaperture image and a low-resolution subaperture image, wherein the high-resolution subaperture image and the low-resolution subaperture image were captured simultaneously from a camera using dissimilar focal lengths, predict a high-resolution predicted disparity map from the high-resolution subaperture image using a neural network, predict a low-resolution predicted disparity map from the low-resolution subaperture image using the neural network, and generate an integrated range map from the high-resolution and low-resolution predicted disparity maps, wherein the integrated range map includes an array of range information that corresponds to the multi-aperture image set and that is generated by overlaying common points in both the high-resolution predicted disparity map and the low-resolution predicted disparity map.


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