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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.

Patent No.:

US 12586204 B1

PDFFull Text
Date of Patent:
Mar. 24, 2026

Filed:

Aug. 02, 2023

Detecting optical discrepancies in captured images

Applicant:

Skydio, Inc., San Mateo, CA (US);

Inventors:

Ryan Kennedy, San Francisco, CA (US);

Peter Henry, San Francisco, CA (US);

Abraham Bachrach, Emerald Hills, CA (US);

Assignee:

Skydio, Inc., San Mateo, CA (US);

Attorney:
Primary Examiner:

Soo Shin

Int. Cl.
CPC ...
G06T 7/11 (2017.01); B64U 10/14 (2023.01); B64U 30/20 (2023.01); B64U 101/30 (2023.01); G05D 1/00 (2024.01); G06T 5/70 (2024.01); G06T 7/00 (2017.01); H04N 13/00 (2018.01); H04N 13/239 (2018.01); H04N 17/00 (2006.01); H04N 23/45 (2023.01); H04N 23/69 (2023.01); H04N 23/71 (2023.01); H04N 23/81 (2023.01); H04N 23/90 (2023.01);
U.S. Cl.
CPC ...
G06T 7/11 (2017.01); G05D 1/102 (2013.01); G06T 5/70 (2024.01); G06T 7/0002 (2013.01); H04N 13/00 (2013.01); H04N 13/239 (2018.05); H04N 17/002 (2013.01); H04N 23/45 (2023.01); H04N 23/69 (2023.01); H04N 23/71 (2023.01); H04N 23/811 (2023.01); H04N 23/90 (2023.01); B64U 10/14 (2023.01); B64U 30/20 (2023.01); B64U 2101/30 (2023.01); B64U 2201/10 (2023.01); G06T 2207/10012 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/30168 (2013.01);
Abstract

Embodiments are described for detecting optical discrepancies associated with image capture analyzing pixels in multiple images corresponding to common points of reference in a physical environment. In an embodiment, photometric error values are averaged over time to compute the mean error at each pixel. Once the estimate of the mean error has a sufficient number of updates above a specified value, the estimate is thresholded to provide a mask of any optical discrepancies occurring in the stereo pair of images. Applications include detecting optical discrepancies in images captured for use by a visual navigation system in guiding an autonomous vehicle (e.g., an unmanned aerial vehicle).

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