IP Library Granted Patent US 11,328,436
Granted Patent B2
US 11,328,436 · App. 17/396,297 · Granted May 10, 2022

Using camera effect in the generation of custom synthetic data for use in training an artificial intelligence model to produce an image depth map

Inventors: Tobias B. Schmidt (Wellington, NZ); Erik B. Edlund (Wellington, NZ); Dejan Momcilovic (Wellington, NZ); Josh Hardgrave (Wellington, NZ)
Assignee: Unity Technologies SF
G06T7/50G06T2207/20081G06T2207/20084
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Quick Facts
Patent No.
US 11,328,436
App. No.
17/396,297
Granted
May 10, 2022
Kind
B2
Abstract

Embodiments allow camera effects, such as imaging noise, to be included in a generation of a synthetic data set for use in training an artificial intelligence model to produce an image depth map. The image depth map can then be employed to assist in compositing live action images from an image capture device with computer generated images in real-time or near real-time. The two types of images (live action and computer generated) are composited accurately by using a depth map. In an embodiment, the depth map includes a “depth value” for each pixel in the live action image. In an embodiment, steps of one or more of feature extraction, matching, filtering or refinement can be implemented, at least in part, with an artificial intelligence (AI) computing approach using a deep neural network with training.

Claims (30)

1. A method for generating custom synthetic data for use in training an artificial intelligence model to produce an image depth map, the method comprising:

obtaining custom recorded data of an aspect of an environment;

obtaining a camera effect measurement of a particular camera;

modifying the aspect in a computer program to create a rendering of a modified environment;

using the camera effect measurement in the rendering;

generating custom synthetic data from the modified environment; and

providing the custom synthetic data to the artificial intelligence model to produce the image depth map.

2. The method of claim 1 , wherein the particular camera is used to capture live-action images of an event for which the image depth map is used.

3. The method of claim 1 , wherein the camera effect includes camera noise.

4. The method of claim 3 , wherein the camera noise is measured from the particular camera.

5. The method of claim 3 , further comprising:

performing a frequency response analysis of characteristics of the camera noise.

6. The method of claim 5 , further comprising:

matching the characteristics in the synthetic data.

7. An apparatus for generating custom synthetic data for use in training an artificial intelligence model to produce an image depth map, the apparatus comprising:

one or more digital processors;

a tangible processor-readable medium including instructions for:

obtaining custom recorded data of an aspect of an environment;

obtaining a camera effect measurement of a particular camera;

modifying the aspect in a computer program to create a rendering of a modified environment;

using the camera effect measurement in the rendering;

generating custom synthetic data from the modified environment; and

providing the custom synthetic data to the artificial intelligence model to produce the image depth map.

8. The apparatus of claim 7 , wherein the particular camera is used to capture live-action images of an event for which the image depth map is used.

9. The apparatus of claim 7 , wherein the camera effect includes camera noise.

10. The apparatus of claim 9 , wherein the camera noise is measured from the particular camera.

11. The apparatus of claim 9 , further comprising:

performing a frequency response analysis of characteristics of the camera noise.

12. The apparatus of claim 11 , further comprising:

matching the characteristics in the synthetic data.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 9, 2022
From: UNITY SOFTWARE INC.
To: UNITY TECHNOLOGIES SF
Reel/Frame 058980/0342 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 8, 2022
From: WETA DIGITAL LIMITED
To: UNITY SOFTWARE INC.
Reel/Frame 058978/0865 →
Continuity (5)
Continuation 17133429 · Dec 23, 2020
Continuation 17081843 · Oct 27, 2020
Provisional Application 62968041 · Jan 30, 2020
Provisional Application 62968035 · Jan 30, 2020
Related Publication 20210366138A1 · Nov 25, 2021
Cited By (1)
US 12,536,778