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:
Jan. 16, 2024

Filed:

Aug. 25, 2021
Applicant:

Genpact Luxembourg S.à R.l. Ii, Luxembourg, LU;

Inventors:

Abhilash Nvs, Bhubaneswar, IN;

Ankit Sati, New Delhi, IN;

Payanshi Jain, Jaipur, IN;

Koundinya K. Nvss, Tirupati, IN;

Rajat Katiyar, Lucknow, IN;

Mohiuddin Khan, Bangalore, IN;

Chirag Jain, Bangalore, IN;

Sreekanth Menon, Bangalore, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06T 7/62 (2017.01); G06F 18/22 (2023.01);
U.S. Cl.
CPC ...
G06T 7/0002 (2013.01); G06F 18/22 (2023.01); G06T 7/11 (2017.01); G06T 7/62 (2017.01); G06T 2207/20081 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30252 (2013.01);
Abstract

A method for dimension estimation based on duplication identification. In some embodiments, the method includes receiving a set of images of an object. The method then includes detecting, using a first machine learning system trained to perform image segmentation, a first image segmentation representing a damage of the object on a first image and a second image segmentation representing a damage of the object on a second image. The method further includes determining, using a second machine learning system trained to perform dimension estimation, a first dimension for the damage represented by the first image segmentation and a second dimension for the damage represented by the second image segmentation. The method includes determining whether the first and second image segmentations represent a same damage. If these image segmentations represent the same damage, the method intelligently combines the first and second dimensions to obtain a final dimension for the damage.


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