Patents by Inventor Erzhuo Che

Erzhuo Che 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).

  • Apparatus and method for detecting intersection edges
    Patent number: 11965967
    Abstract: A computer implemented scheme for a light detection and ranging (LIDAR) system where point cloud feature extraction and segmentation by efficiently is achieved by: (1) data structuring; (2) edge detection; and (3) region growing.
    Type: Grant
    Filed: November 16, 2022
    Date of Patent: April 23, 2024
    Assignee: Oregon State University
    Inventors: Erzhuo Che, Michael Olsen
  • Apparatus and method for efficient scanner trajectory reconstruction from mobile LIDAR point cloud
    Patent number: 11885911
    Abstract: An efficient approach to reconstruct the scanner trajectory of the mobile LIDAR system from the point cloud with minimal user parameters. The process of reconstructing trajectory comprises four steps: (1) spin rate estimation, (2) scan plane estimation, (3) scan origin estimation, and (4) global smoothing.
    Type: Grant
    Filed: July 30, 2020
    Date of Patent: January 30, 2024
    Assignee: OREGON STATE UNIVERSITY
    Inventors: Erzhuo Che, Michael Olsen
  • APPARATUS AND METHOD FOR DETECTING INTERSECTION EDGES
    Publication number: 20230098480
    Abstract: A computer implemented scheme for a light detection and ranging (LIDAR) system where point cloud feature extraction and segmentation by efficiently is achieved by: (1) data structuring; (2) edge detection; and (3) region growing.
    Type: Application
    Filed: November 16, 2022
    Publication date: March 30, 2023
    Applicant: Oregon State University
    Inventors: Erzhuo Che, Michael Olsen
  • Apparatus and method for efficient point cloud feature extraction and segmentation framework
    Patent number: 11567207
    Abstract: A computer implemented scheme for a light detection and ranging (LIDAR) system where point cloud feature extraction and segmentation by efficiently is achieved by: (1) data structuring; (2) edge detection; and (3) region growing.
    Type: Grant
    Filed: July 30, 2020
    Date of Patent: January 31, 2023
    Assignee: Oregon State University
    Inventors: Erzhuo Che, Michael Olsen
  • METHOD AND APPARATUS TO EXTRACT POWERLINES FROM LIDAR POINT CLOUD DATA
    Publication number: 20220292761
    Abstract: An efficient and robust approach for powerline point extraction and refinement is described. In the candidate powerline point extraction step, a voxel-based subsampling structure temporarily substitutes the original scan points with regularly spaced subsampled points that still preserve key details present within the point cloud but significantly reduce the dataset size. After removing the ground surface and adjacent objects, candidate powerline points are efficiently extracted through a hierarchical, feature-based filtering process. In the refinement step, the link between the subsampled candidate powerline points and original scan point cloud enable the original points to be segmented and grouped into clusters. By fitting mathematical models, an individual powerline is re-clustered and used to reconstruct the broken sections in the powerlines.
    Type: Application
    Filed: March 7, 2022
    Publication date: September 15, 2022
    Applicant: Oregon State University
    Inventors: Jaehoon Jung, Michael J. Olsen, Erzhuo Che
  • APPARATUS AND METHOD FOR EFFICIENT POINT CLOUD FEATURE EXTRACTION AND SEGMENTATION FRAMEWORK
    Publication number: 20210048530
    Abstract: A computer implemented scheme for a light detection and ranging (LIDAR) system where point cloud feature extraction and segmentation by efficiently is achieved by: (1) data structuring; (2) edge detection; and (3) region growing.
    Type: Application
    Filed: July 30, 2020
    Publication date: February 18, 2021
    Applicant: Oregon State University
    Inventors: Erzhuo Che, Michael Olsen
  • APPARATUS AND METHOD FOR EFFICIENT SCANNER TRAJECTORY RECONSTRUCTION FROM MOBILE LIDAR POINT CLOUD
    Publication number: 20210048512
    Abstract: An efficient approach to reconstruct the scanner trajectory of the mobile LIDAR system from the point cloud with minimal user parameters. The process of reconstructing trajectory comprises four steps: (1) spin rate estimation, (2) scan plane estimation, (3) scan origin estimation, and (4) global smoothing.
    Type: Application
    Filed: July 30, 2020
    Publication date: February 18, 2021
    Applicant: Oregon State University
    Inventors: Erzhuo Che, Michael Olsen