US 2026/0017815 A1 · Machine Learning Model-Based 2-D Pose Prediction and Correction

Abstract

A system includes a hardware processor, a machine learning (ML) model trained to predict two-dimensional (2-D) poses and a graphical user interface (GUI). The hardware processor is configured to receive at least one partial pose input representing a 2-D partial pose of a subject, display, via the GUI, the 2-D partial pose, and receive, via the GUI, at least one user input responsive to the display of the 2-D partial pose. The hardware processor is further configured to predict, using the ML model and in response to receiving the at least one user input, a 2-D full pose of the subject, to provide a predicted 2-D full pose having a plurality of keypoints, and display, via the GUI, the predicted 2-D full pose and the plurality of keypoints.

Claims20

Dependent claims

A system comprising:

a hardware processor;
and
a machine learning (ML) model trained to predict two-dimensional (2-D) poses;
and
a graphical user interface (GUI);
the hardware processor configured to:
receive at least one partial pose input representing a 2-D partial pose of a subject;
display, via the GUI, the 2-D partial pose;
receive, via the GUI, at least one user input responsive to the display of the 2-D partial pose;
predict, using the ML model, in response to receiving the at least one user input, a 2-D full pose of the subject, to provide a predicted 2-D full pose having a plurality of keypoints;
and
display, via the GUI, the predicted 2-D full pose and the plurality of keypoints.

9 more elements

A method for use by a system including a hardware processor, a machine learning (ML) model trained to predict two-dimensional (2-D) poses and a graphical user interface (GUI), the method comprising:

receiving, using the hardware processor, at least one partial pose input representing a 2-D partial pose of a subject;
displaying via the GUI, using the hardware processor, the 2-D partial pose;
receiving via the GUI, using the hardware processor, at least one user input responsive to the display of the 2-D partial pose;
predicting, using the hardware processor and using the ML model, in response to receiving the at least one user input, a 2-D full pose of the subject, to provide a predicted 2-D full pose having a plurality of keypoints;
and
displaying via the GUI, using the hardware processor, the predicted 2-D full pose and the plurality of keypoints.

3 more elements

Dependencies are inferred from the claim text.

Machine Learning Model-Based 2-D Pose Prediction and Correction

Life of this patent

Machine Learning Model-Based 2-D Pose Prediction and Correction

Life of this patent

Abstract

Claims20