US 11,113,572 B2 · Systems, methods, and storage media for evaluating images

Abstract

Embodiments may: select a set of training images; extract a first set of features from each training image of the set of training images to generate a first feature tensor for each training image; extract a second set of features from each training image to generate a second feature tensor for each training image; reduce a dimensionality of each first feature tensor to generate a first modified feature tensor for each training image; reduce a dimensionality of each second feature tensor to generate a second modified feature tensor for each training image; construct a first generative model representing the first set of features and a second generative model representing the second set of features of the set of training images; identify a first candidate image; and apply a regression algorithm to the first candidate image and each of the first generative model and the second generative model to determine whether the first candidate image is similar to the set of training images.

Claims20

Dependent claims

A system comprising:

one or more hardware processors including machine-readable instructions to:
identify a first image;
extract a first set of features from the first image to generate a first feature tensor for the first image;
extract a second set of features from the first image to generate a second feature tensor for the first image;
identify a second image;
extract a third set of features from the second image to generate a third feature tensor for the second image;
extract a fourth set of features from the second image to generate a fourth feature tensor for the second image;
apply a first regression analysis to determine a first geometrical distance between the first feature tensor of the first image and the third feature tensor of the second image;
apply a second regression analysis to determine a second geometrical distance between the second feature tensor of the first image and the fourth feature tensor of the second image;
and
determine a similarity between the first image and the second image based on the first geometrical distance and the second geometrical distance.

8 more elements

A non-transitory computer-readable storage medium having instructions embodied thereon, the instructions being executable by one or more processors to perform a method comprising:

identifying a first image;
extracting a first set of features from the first image to generate a first feature tensor for the first image;
extracting a second set of features from the first image to generate a second feature tensor for the first image;
identifying a second image;
extracting a third set of features from the second image to generate a third feature tensor for the second image;
extracting a fourth set of features from the second image to generate a fourth feature tensor for the second image;
applying a first regression analysis to determine a first geometrical distance between the first feature tensor of the first image and the third feature tensor of the second image;
applying a second regression analysis to determine a second geometrical distance between the second feature tensor of the first image and the fourth feature tensor of the second image;
and
determining a similarity between the first image and the second image based on the first geometrical distance and the second geometrical distance.

7 more elements

Dependencies are inferred from the claim text.

Systems, methods, and storage media for evaluating images

Life of this patent

Systems, methods, and storage media for evaluating images

Life of this patent

Abstract

Claims20