US 12,488,562 B2
Systems and methods for fractal-based visual searching
Amiteshwar Dayal Seth, Bangalore (IN)
Assigned to Accenture Global Solutions Limited, Dublin (IE)
Filed by Accenture Global Solutions Limited, Dublin (IE)
Filed on Nov. 29, 2021, as Appl. No. 17/536,400.
Claims priority of provisional application 63/120,135, filed on Dec. 1, 2020.
Prior Publication US 2022/0172455 A1, Jun. 2, 2022
Int. Cl. G06V 10/74 (2022.01); G06F 16/532 (2019.01); G06N 20/00 (2019.01); G06V 10/42 (2022.01); G06V 10/44 (2022.01); G06V 10/77 (2022.01); G06V 10/82 (2022.01)
CPC G06V 10/761 (2022.01) [G06F 16/532 (2019.01); G06N 20/00 (2019.01); G06V 10/42 (2022.01); G06V 10/44 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01)] 16 Claims
OG exemplary drawing
 
1. A method for performing a visual search based on a query image, the method comprising:
receiving, by one or more processors, the query image;
applying, by the one or more processors, a fractal transform to the query image;
determining, by the one or more processors, an immediate search space based on the fractal transform of the query image, wherein the immediate search space corresponds to a subset of a plurality of images stored in a dataset;
applying, by the one or more processors, deep learning logic to the query image to produce a feature set for the query image,
wherein the feature set includes information associated with features of the query image;
evaluating, by the one or more processors, the feature set of the query image against feature sets of the subset of the plurality of images included in the immediate search space to determine a set of search results,
wherein the set of search results comprises one or more images from the subset of the plurality of images having features similar to the query image;
retrieving the features sets of the subset of the plurality of images included in the immediate search space from a memory based on the fractal transform of the query image,
wherein the feature set of the query image is determined using one or more kernels of a visual search engine, and
wherein a first portion of the feature set of the query image is obtained from the query image, a second portion of the feature set is obtained from a first derived set of images during training of the visual search engine, and a third portion of the feature set is obtained from a second derived set of images during training of the visual search engine; and
outputting, by the one or more processors, the set of search results.