US 12,293,563 B2 · Automated data annotation for computer vision applications

Abstract

This disclosure provides methods, devices, and systems for training machine learning models. The present implementations more specifically relate to techniques for automating the annotation of data for training machine learning models. In some aspects, a machine learning system may receive a reference image depicting an object of interest with one or more annotations and also may receive one or more input images depicting the object of interest at various distances, angles, or locations but without annotations. The machine learning system maps a set of points in the reference image to a respective set of points in each input image so that the annotations from the reference image are projected onto the object of interest in each input image. The machine learning system may further train a machine learning model to produce inferences about the object of interest based on the annotated input images.

Claims20

Dependent claims

A method of training a machine learning model, comprising:

receiving a first input image depicting an object of interest and a planar extension object attached thereto, the planar extension object having a planar surface that is coplanar with a surface of the object of interest;
receiving a reference image depicting the object of interest and one or more annotations associated with the object of interest;
mapping a plurality of first points in the reference image to a respective plurality of second points in the first input image so that the one or more annotations in the reference image are projected onto the object of interest in the first input image, wherein one or more first points of the plurality of first points and one or more second points of the plurality of second points coincide with the planar surface;
and
training the machine learning model to produce inferences from images depicting the object of interest based at least in part on the mapping of the plurality of first points to the plurality of second points.

2 more elements

A machine learning system comprising:

a processing system;
and
a memory storing instructions that, when executed by the processing system, causes the machine learning system to:
receive a first input image depicting an object of interest and a planar extension object attached thereto, the planar extension object having a planar surface that is coplanar with a surface of the object of interest;
receive a reference image depicting the object of interest and one or more annotations associated with the object of interest;
map a plurality of first points in the reference image to a respective plurality of second points in the first input image so that the one or more annotations in the reference image are projected onto the object of interest in the first input image, wherein one or more first points of the plurality of first points and one or more second points of the plurality of second points coincide with the planar surface;
and
train the machine learning model to produce inferences from images depicting the object of interest based at least in part on the mapping of the plurality of first points to the plurality of second points.

5 more elements

Dependencies are inferred from the claim text.

Automated data annotation for computer vision applications

Life of this patent

Automated data annotation for computer vision applications

Life of this patent

Abstract

Claims20