Invention Grant
- Patent Title: Methods and systems for applying machine learning to volumetric capture of a body in a real-world scene
-
Application No.: US16830848Application Date: 2020-03-26
-
Publication No.: US11222474B2Publication Date: 2022-01-11
- Inventor: Daniel Kopeinigg , Andrew Walkingshaw , Arthur van Hoff , Charles LePere , Christopher Redmann , Philip Lee , Solmaz Hajmohammadi , Sourabh Khire , Simion Venshtain
- Applicant: Verizon Patent and Licensing Inc.
- Applicant Address: US VA Arlington
- Assignee: Verizon Patent and Licensing Inc.
- Current Assignee: Verizon Patent and Licensing Inc.
- Current Assignee Address: US VA Arlington
- Main IPC: G06T7/70
- IPC: G06T7/70 ; G06T19/00 ; G06T13/40 ; G06T17/20 ; G06K9/00 ; G06N20/00 ; G06T15/04 ; G06T15/08

Abstract:
An illustrative volumetric capture system accesses a machine learning model associated with bodies of a particular body type, as well as a two-dimensional (2D) image captured by a capture device located at a real-world scene. The 2D image depicts a body of the particular body type that is present at the real-world scene. Using the machine learning model and based on the 2D image, the volumetric capture system identifies a 2D joint location, from a perspective of the capture device, of a particular joint of the body. The volumetric capture system also generates a three-dimensional (3D) reference model of the body that represents the particular joint of the body at a 3D joint location that is determined based on the 2D joint location identified using the machine learning model. Corresponding methods and systems are also disclosed.
Public/Granted literature
- US20200312011A1 Methods and Systems for Applying Machine Learning to Volumetric Capture of a Body in a Real-World Scene Public/Granted day:2020-10-01
Information query