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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 11587221 B1

PDFFull Text
Date of Patent:
Feb. 21, 2023

Filed:

May. 20, 2021

Detailed damage determination with image cropping

Applicant:

Tractable Ltd, London, GB;

Inventors:

Razvan Ranca, London, GB;

Marcel Horstmann, London, GB;

Bjorn Mattsson, London, GB;

Janto Oellrich, London, GB;

Yih Kai Teh, London, GB;

Ken Chatfield, London, GB;

Franziska Kirschner, London, GB;

Rusen Aktas, London, GB;

Laurent Decamp, London, GB;

Mathieu Ayel, London, GB;

Julia Peyre, London, GB;

Shaun Trill, London, GB;

Crystal Van Oosterom, London, GB;

Assignee:

TRACTABLE LIMITED, London, GB;

Attorney:

Fay Kaplun & Marcin, LLP

Primary Examiner:

John W Lee

Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06F 16/2457 (2019.01); G06F 40/20 (2020.01); G06K 9/62 (2022.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06Q 40/08 (2012.01); G06N 3/049 (2023.01); G06Q 10/20 (2023.01); G06Q 10/0875 (2023.01); G06T 7/11 (2017.01); G06Q 10/0631 (2023.01); G06Q 30/0283 (2023.01); G06V 10/22 (2022.01); G06V 10/20 (2022.01); G06V 20/10 (2022.01); G06V 10/82 (2022.01); G06Q 30/016 (2023.01); G06V 10/25 (2022.01);
U.S. Cl.
CPC ...
G06T 7/0004 (2013.01); G06F 16/24578 (2019.01); G06F 40/20 (2020.01); G06K 9/628 (2013.01); G06K 9/6219 (2013.01); G06K 9/6227 (2013.01); G06K 9/6256 (2013.01); G06K 9/6257 (2013.01); G06K 9/6267 (2013.01); G06K 9/6277 (2013.01); G06K 9/6281 (2013.01); G06N 3/04 (2013.01); G06N 3/049 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06Q 10/06313 (2013.01); G06Q 10/0875 (2013.01); G06Q 10/20 (2013.01); G06Q 30/0283 (2013.01); G06T 7/0002 (2013.01); G06T 7/11 (2017.01); G06V 10/22 (2022.01); G06V 10/225 (2022.01); G06V 10/255 (2022.01); G06V 10/82 (2022.01); G06V 20/10 (2022.01); G06Q 30/016 (2013.01); G06Q 40/08 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20132 (2013.01); G06T 2207/30156 (2013.01); G06T 2207/30164 (2013.01); G06T 2207/30248 (2013.01); G06T 2207/30252 (2013.01); G06V 10/25 (2022.01); G06V 2201/08 (2022.01); G06V 2201/10 (2022.01);
Abstract

The present invention relates to the determination of damage to portions of a vehicle. More particularly, the present invention relates to determining whether each part of a vehicle should be classified as damaged or undamaged and optionally the severity of the damage to each part of the damaged vehicle including preserving the quality of the input images of the damage to the vehicle. Aspects and/or embodiments seek to provide a computer-implemented method for determining damage states of each part of a damaged vehicle, indicating whether each part of the vehicle is damaged or undamaged and optionally the severity of the damage to each part of the damaged vehicle, using images of the damage to the vehicle and trained models to assess the damage indicated in the images of the damaged vehicle, including preserving the quality and/or resolution of the images of the damaged vehicle.

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