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:
Feb. 27, 2024

Filed:

Apr. 09, 2019
Applicant:

Hewlett-packard Development Company, L.p., Spring, TX (US);

Inventors:

Jose Luis Abad Peiro, Sant Cugat del Valles, ES;

Md Imbesat Hassan Rizvi, Bangalore, IN;

Niranjan Damera Venkata, Chennai, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/56 (2019.01); G06F 16/55 (2019.01); G06F 16/583 (2019.01); G06V 10/94 (2022.01); G06N 3/02 (2006.01); G06F 18/2413 (2023.01); G06F 18/22 (2023.01); G06F 18/2415 (2023.01); G06F 18/2431 (2023.01); G06V 10/74 (2022.01); G06V 10/762 (2022.01); G06V 10/764 (2022.01); G06V 20/00 (2022.01);
U.S. Cl.
CPC ...
G06F 16/56 (2019.01); G06F 16/55 (2019.01); G06F 16/583 (2019.01); G06F 18/22 (2023.01); G06F 18/2415 (2023.01); G06F 18/2431 (2023.01); G06F 18/24147 (2023.01); G06N 3/02 (2013.01); G06V 10/761 (2022.01); G06V 10/763 (2022.01); G06V 10/764 (2022.01); G06V 10/95 (2022.01); G06V 20/35 (2022.01);
Abstract

Disclosed herein is a method of determining a user profile based on a set of user-selected images, a method of selecting images from an image database of digital images based on a user profile, a computer system and a computer program product. The method of determining a user profile comprises obtaining a set of reference images, wherein each of the reference images is associated with a category from a plurality of categories; determining a sample feature vector for a sample image and a reference feature vector for each of the reference images, wherein the feature vector of an image is associated to features of the image; determining a similarity metric between the sample image and each of the reference images based on the sample feature vector and the reference feature vectors; selecting nearest reference images for each category, wherein the similarity metric between the sample image and a nearest reference image meets a minimum assignment similarity criterion and a maximum assignment similarity criterion; and determining the user profile by calculating an assignment probability for each category based on the similarity metrics between the sample image and the nearest reference images of the respective category.


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