Compressed representations for appearance of fiber-based digital assets

Patent metadata

Field	Value
Publication number	US-2025029323-A1
Application number	US-202318354855-A
Country	US
Kind code	A1
Filing date	Jul 19, 2023
Priority date	Jul 19, 2023
Publication date	Jan 23, 2025
Grant date	—

Abstract

Techniques for generation of compressed representations for appearance of fiber-based digital assets are described that support computationally efficient and high fidelity rendering of digital assets that include fiber primitives under a variety of lighting conditions and view directions. A processing device, for instance, receives a digital asset that includes fiber primitives to be included in a three-dimensional digital scene. The processing device generates a compressed representation of the digital asset that maintains a geometry of the digital asset and includes a precomputed light transport. The processing device then inserts the compressed representation into the digital scene, such as at a location relative to one or more light sources. The content processing system applies one or more lighting effects to the compressed representation based on the precomputed light transport and the location relative to the one or more light sources.

First claim

What is claimed is:

1 . A method comprising:
receiving, by a processing device, a digital asset to be included in a three-dimensional digital scene, the digital asset including fiber primitives; generating, by the processing device, a compressed representation of the digital asset that includes a precomputed light transport for the fiber primitives; inserting, by the processing device, the compressed representation of the digital asset into a location relative to a digital light source within the three-dimensional digital scene; and applying, by the processing device, one or more lighting effects to the fiber primitives based on the precomputed light transport and the location relative to the digital light source.

2 . The method as described in claim 1 , wherein the applying the one or more lighting effects is based on a view direction of the compressed representation within the three-dimensional digital scene.

3 . The method as described in claim 1 , wherein the applying the one or more lighting effects includes determining an intersection point of a ray traced from a virtual camera that defines a view direction with a fiber primitive of the compressed representation and computing a color value to apply to the fiber primitive at the intersection point based on the precomputed light transport.

4 . The method as described in claim 3 , wherein the compressed representation includes a feature grid that parameterizes a geometry of the fiber primitives and a multilayer perceptron, and wherein the applying the one or more lighting effects includes extracting a feature vector from the feature grid based on the intersection point and evaluating the feature vector using the multilayer perceptron to determine the color value.

5 . The method as described in claim 4 , wherein the feature vector is combined with a view direction, a light direction, a fiber direction, and a fiber axis offset for the intersection point for input to the multilayer perceptron.

6 . The method as described in claim 1 , further comprising generating a training dataset that includes training images depicting the digital asset viewed from a plurality of different locations within the three-dimensional digital scene.

7 . The method as described in claim 6 , wherein generating the compressed representation includes utilizing the training dataset to adjust weights of a multi-layer perceptron of the compressed representation and update a feature grid of the compressed representation.

8 . The method as described in claim 1 , wherein the precomputed light transport represents a scattering interaction of light rays that interact with the fiber primitives.

9 . The method as described in claim 1 , wherein the applying the one or more lighting effects includes applying RGB color values to points along the fiber primitives.

10 . A system comprising:
a memory component; and a processing device coupled to the memory component, the processing device to perform operations comprising:
receiving a digital asset to be included in a three-dimensional digital scene, the digital asset including fiber primitives;
generating a compressed representation of the digital asset that includes a precomputed light transport for the fiber primitives;
inserting the compressed representation of the digital asset into a location relative to a digital light source within the three-dimensional digital scene; and
applying one or more lighting effects to the fiber primitives based on the precomputed light transport and the location relative to the digital light source.

11 . The system as described in claim 10 , wherein applying the one or more lighting effects is based on a view direction of the compressed representation within the three-dimensional digital scene.

12 . The system as described in claim 10 , wherein the applying the one or more lighting effects includes determining an intersection point of a ray traced from a virtual camera that defines a view direction with a fiber primitive of the compressed representation and computing a color value to apply to the fiber primitive at the intersection point based on the precomputed light transport.

13 . The system as described in claim 12 , wherein the compressed representation includes a feature grid that parameterizes a geometry of the fiber primitives and a multilayer perceptron, and wherein the applying the one or more lighting effects includes extracting a feature vector from the feature grid based on the intersection point and evaluating the feature vector using the multilayer perceptron to determine the color value.

14 . The system as described in claim 13 , wherein the feature vector represents a view direction, a light direction, a fiber direction, and a fiber axis offset for the intersection point.

15 . The system as described in claim 10 , the operations further comprising generating a training dataset that includes training images depicting the digital asset viewed from a plurality of different locations within the three-dimensional digital scene.

16 . The system as described in claim 15 , wherein generating the compressed representation includes utilizing the training dataset to adjust weights of a multi-layer perceptron of the compressed representation and update a feature grid of the compressed representation.

17 . A non-transitory computer-readable medium storing executable instructions, which when executed by a processing device, cause the processing device to perform operations comprising:
receiving a digital asset to be included in a three-dimensional digital scene; generating a compressed representation of the digital asset that includes a precomputed light transport for the digital asset; inserting the compressed representation of the digital asset into a location relative to a digital light source within the three-dimensional digital scene; and displaying the compressed representation with one or more lighting effects applied based on the precomputed light transport and the location relative to the digital light source.

18 . The non-transitory computer-readable medium as described in claim 17 , further comprising changing a condition of the digital light source and updating the one or more lighting effects based on the changed condition of the digital light source, the condition including one or more of an intensity of the digital light source, a spatial location of the digital light source within the three-dimensional digital scene, or a type of illumination of the digital light source.

19 . The non-transitory computer-readable medium as described in claim 17 , further comprising changing a view direction of the compressed representation in the three-dimensional digital scene and updating the one or more lighting effects based on the changed view direction.

20 . The non-transitory computer-readable medium as described in claim 17 , wherein the digital asset defines a three-dimensional representation of a granular media.

Assignees

• Adobe Inc

Inventors

• Lakshminarayana Krishna Bhargava Mullia
• Sun Xin
• Hašan Miloš
• Luan fujun

Classifications

• G06T15/06

  Ray-tracing · CPC title

• G06T15/005

  General purpose rendering architectures · CPC title

• G06T15/506 Primary

  Illumination models · CPC title

• G06T2210/21

  Collision detection, intersection · CPC title

• G06T2210/56

  Particle system, point based geometry or rendering · CPC title