GENERATING ENHANCED THREE-DIMENSIONAL OBJECT RECONSTRUCTION MODELS FROM SPARSE SET OF OBJECT IMAGES

Patent №

US 11,669,986

Granted

2023-06-06

Filed 2021

Owner

ADOBE INC.

+1 more

AI components

2

ml · vision

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

17233122

Enhanced methods and systems for generating both a geometry model and an optical-reflectance model (an object reconstruction model) for a physical object, based on a sparse set of images of the object under a sparse set of viewpoints. The geometry model is a mesh model that includes a set of vertices representing the object's surface. The reflectance model is SVBRDF that is parameterized via multiple channels (e.g., diffuse albedo, surface-roughness, specular albedo, and surface-normals). For each vertex of the geometry model, the reflectance model includes a value for each of the multiple channels. The object reconstruction model is employed to render graphical representations of a virtualized object (a VO based on the physical object) within a computation-based (e.g., a virtual or immersive) environment. Via the reconstruction model, the VO may be rendered from arbitrary viewpoints and under arbitrary lighting conditions.

Machine learningVisionG06T 7/514G06T 7/596G06T 17/20H04N 13/111H04N 13/128H04N 13/271H04N 13/275H04N 13/282+6 more

AI classification

Vision1.00
Machine learning0.82
AI hardware0.26
Knowledge representation0.06
Evolutionary computation0.00
Speech0.00
Natural language0.00
Planning0.00

Ownership

ADOBE INC.

assignment · 563720059

THE REGENTS OF THE UNIVERSITY OF CALIFORNIA

assignment · 573450320

Assignors

SUNKAVALLI, KALYAN KRISHNA

On an employer assignment, the assignors are typically the inventors.

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