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:
Jul. 15, 2025

Filed:

Oct. 09, 2023
Applicant:

Mftb Holdco, Inc., Seattle, WA (US);

Inventors:

Naji Khosravan, Seattle, WA (US);

Sing Bing Kang, Seattle, WA (US);

Ivaylo Boyadzhiev, Seattle, WA (US);

Pierre Moulon, Seattle, WA (US);

Yujie Li, Seattle, WA (US);

Assignee:

MFTB Holdco, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G01S 17/89 (2020.01); G06F 16/54 (2019.01); G06F 16/587 (2019.01); G06F 30/13 (2020.01); G06N 20/00 (2019.01); G06Q 30/02 (2023.01); G06Q 30/0283 (2023.01); G06Q 50/16 (2012.01); G06T 7/174 (2017.01); G06T 7/73 (2017.01); G06T 11/00 (2006.01); G06V 10/60 (2022.01); G06V 20/10 (2022.01);
U.S. Cl.
CPC ...
G06Q 30/0278 (2013.01); G01S 17/89 (2013.01); G06F 16/54 (2019.01); G06F 16/587 (2019.01); G06F 30/13 (2020.01); G06N 20/00 (2019.01); G06Q 30/0283 (2013.01); G06Q 50/16 (2013.01); G06T 7/0002 (2013.01); G06T 7/174 (2017.01); G06T 7/73 (2017.01); G06T 11/00 (2013.01); G06T 2210/04 (2013.01); G06V 10/60 (2022.01); G06V 20/176 (2022.01); G06V 20/182 (2022.01); G06V 20/188 (2022.01);
Abstract

A valuation system to identify interior features of a property, identify exterior features related to interior features using aerial images, and to generate property valuations based on the identified features is provided. The valuation system identifies, using a computer vision module, interior features based on interior image data (e.g., photos) of a property, and further identifies exterior features associated with any of the interior features based on an aerial photo of the property. For example, trees and buildings (e.g., exterior features) adjacent to a window (e.g., an interior feature) can be identified by a computer vision module through the combination of interior and exterior image data. In other words, the identification of property features by the computer vision module can be enriched by correlating interior image data (e.g., photos, video walkthroughs) to exterior image data (e.g., satellite photos, aerial photos).


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