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US 2021/0233273 A1Published application
Determining a 3-d hand pose from a 2-d image using machine learning
AssigneeNVIDIA Corporation
InventorsAdrian Spurr, Pavlo Molchanov, Umar Iqbal, Jan Kautz
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Abstract
Apparatuses, systems, and techniques that determine the pose of a human hand from a 2-D image are described herein. In at least one embodiment, training of a neural network is augmented using weakly labeled or unlabeled pose data which is augmented with losses based on a human hand model.
Claims22
A processor, comprising:
- one or more arithmetic logic units (ALUs) to determine a 3-D pose from an image using one or more neural networks, the one or more neural networks trained by at least:
- obtaining a 2-D image of an appendage;
- generating a proposed 3-D pose of the appendage from the 2-D image of the appendage;
- determining one or more losses that are based at least in part on a model that describes allowable appendage positions;
- and
- adjusting the one or more neural networks based at least in part on the one or more losses.
3 more elements
A system, comprising:
- one or more processors to determine a 3-D pose using one or more neural networks trained by at least:
- obtaining a 2-D image of an appendage;
- generating a predicted pose from the 2-D image;
- determining a loss value by at least comparing the predicted pose generated by the one or more neural networks to a distribution of acceptable pose parameters in a kinematic model of a human appendage;
- and
- adjusting the one or more neural networks based on the loss value;
- and
- one or more memories to store the one or more neural networks.
5 more elements
A method, comprising:
- determining a 3-D pose from a 2-D image using one or more neural networks trained, at least in part, by:
- obtaining a 2-D image of an appendage;
- generating a proposed appendage pose from the 2-D image;
- determining a value based at least in part on an evaluation of the proposed appendage pose against a model that describes allowable appendage structure and allowable appendage poses;
- and
- adjusting the one or more neural networks based on the value;
- and
- one or more memories to store the one or more neural networks.
5 more elements
Dependencies are inferred from the claim text.