Patents by Inventor Diane Lingrand

Diane Lingrand has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Keypoint-based point-pair-feature for scalable automatic global registration of large RGB-D scans
    Patent number: 10217277
    Abstract: A method, system, and apparatus provide the ability to globally register point cloud scans. A first and a second three-dimensional (3D) point cloud are acquired. The point clouds have a subset of points in common and there is no prior knowledge on an alignment between the point clouds. Particular points that are likely to be identified in the other point cloud are detected. Information about a normal of each of the detected particular points is retrieved. A descriptor (that only describes 3D information) is built on each of the detected particular points. Matching pairs of descriptors are determined. Rigid transformation hypotheses are estimated (based on the matching pairs) and represent a transformation. The hypotheses are accumulated into a fitted space, selected based on density, and validated based on a scoring. One of the hypotheses is then selected as a registration.
    Type: Grant
    Filed: December 2, 2016
    Date of Patent: February 26, 2019
    Assignee: AUTODESK, INC.
    Inventors: Luc Franck Robert, Nicolas Gros, Yann Noutary, Lucas Malleus, Frederic Precioso, Diane Lingrand
  • KEYPOINT-BASED POINT-PAIR-FEATURE FOR SCALABLE AUTOMATIC GLOBAL REGISTRATION OF LARGE RGB-D SCANS
    Publication number: 20170161945
    Abstract: A method, system, and apparatus provide the ability to globally register point cloud scans. A first and a second three-dimensional (3D) point cloud are acquired. The point clouds have a subset of points in common and there is no prior knowledge on an alignment between the point clouds. Particular points that are likely to be identified in the other point cloud are detected. Information about a normal of each of the detected particular points is retrieved. A descriptor (that only describes 3D information) is built on each of the detected particular points. Matching pairs of descriptors are determined. Rigid transformation hypotheses are estimated (based on the matching pairs) and represent a transformation. The hypotheses are accumulated into a fitted space, selected based on density, and validated based on a scoring. One of the hypotheses is then selected as a registration.
    Type: Application
    Filed: December 2, 2016
    Publication date: June 8, 2017
    Applicant: Autodesk, Inc.
    Inventors: Luc Franck Robert, Nicolas Gros, Yann Noutary, Lucas Malleus, Frederic Precioso, Diane Lingrand