US 2024/0071010 A1 · MECHANISMS FOR RECOGNITION OF OBJECTS AND MATERIALS IN AUGMENTED REALITY APPLICATIONS

Abstract

Training sets of images used for training machine vision systems for object recognition may be augmented via various training set augmentation methods. The machine vision systems trained via the augmented training sets may be further used in an augmented reality procedural guidance system for guiding an operator to complete one or more steps with respect to one or more objects. The training set augmentations may include one or more of an object motion augmentation, a camera motion augmentation, an object herding or clumping augmentation, an object size reduction augmentation, a diversified background augmentation, and a diversified background augmentation with synthetic background images. In some instances, machine vision systems may also be alternatively or concurrently trained to use optically distinguishable markers to recognize objects.

Claims20

Dependent claims

A method, comprising:

creating a training set for training a machine learning algorithm of a machine vision system that detects objects in an environment, the training set including multiple images of an object;
and
applying one or more training set augmentations to each of a plurality of images included in the multiple images of the object to generate additional images that include the object for inclusion in the training set, wherein the one or more training set augmentations include an object motion augmentation, a camera motion augmentation, an object clumping augmentation, an object size reduction augmentation, a first diversified background augmentation, or a second diversified background augmentation with one or more synthetic background images.

One or more non-transitory computer-readable media storing computer-executable instructions that upon execution cause one or more processors to perform acts comprising:

capturing multiple images of an object using at least one of a variety of different cameras, different camera angles, different distances of the different cameras from the object, different light conditions, and different image backgrounds;
labeling the object as captured in the multiple images with corresponding labels by at least segmenting the object in each of the multiple images from a corresponding background based on an inputted polygon with a perimeter that corresponds to one or more boundaries of the object and associates the object that is segmented with a corresponding label;
annotating each of the multiple images with additional annotating information about the object;
compiling the multiple images of the object, the corresponding labels, and the additional annotation information into a training set for training a machine learning algorithm of a machine vision system that detects objects in an environment.

1 more element

Dependencies are inferred from the claim text.

Mechanisms for recognition of objects and materials in augmented reality applications

Life of this patent

Mechanisms for recognition of objects and materials in augmented reality applications

Life of this patent

Abstract

Claims20