System and method for procedurally synthesizing datasets of objects of interest for training machine-learning models
First Claim
1. A system for procedurally synthesizing a training dataset for training a machine-learning model, comprising:
- a training designer configured to describe variations in content of training images to be included in said training dataset; and
an image definer coupled to said training designer, configured to generate training image definitions in accordance with said variations and transmit said training image definitions;
to a 3D graphics engine for rendering into corresponding training images, andto a ground truth generator for generating, at least partially in parallel with the rendering by the 3D graphics engine, associated ground truth corresponding to said training images, said training images and said associated ground truth comprising said training dataset.
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Abstract
A system and method for procedurally synthesizing a training dataset for training a machine-learning model. In one embodiment, the system includes: (1) a training designer configured to describe variations in content of training images to be included in the training dataset and (2) an image definer coupled to the training designer, configured to generate training image definitions in accordance with the variations and transmit the training image definitions: to a 3D graphics engine for rendering into corresponding training images, and further to a ground truth generator for generating associated ground truth corresponding to the training images, the training images and the associated ground truth comprising the training dataset.
36 Citations
20 Claims
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1. A system for procedurally synthesizing a training dataset for training a machine-learning model, comprising:
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a training designer configured to describe variations in content of training images to be included in said training dataset; and an image definer coupled to said training designer, configured to generate training image definitions in accordance with said variations and transmit said training image definitions; to a 3D graphics engine for rendering into corresponding training images, and to a ground truth generator for generating, at least partially in parallel with the rendering by the 3D graphics engine, associated ground truth corresponding to said training images, said training images and said associated ground truth comprising said training dataset. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system for procedurally synthesizing a training dataset for training a machine-learning model, comprising:
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a first processor configured to generate training image definitions in accordance with variations in content of training images to be included in said training dataset; a second processor configured to render corresponding training images from said training image definitions; and a third processor configured to generate, from said training image definitions and at least partially in parallel with said render of said second processor, associated ground truth corresponding to said training images, said training images and said associated ground truth comprising said training dataset. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification