The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 24, 2024

Filed:

Aug. 24, 2021
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Xu Min, Beijing, CN;

Dan Zhang, Beijing, CN;

Xue Ping Liu, Beijing, CN;

Yuan Yuan Ding, Shanghai, CN;

Hong Bing Zhang, Beijing, CN;

Chao Xin, Ningbo, CN;

Fan Li, Xianyang, CN;

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 17/05 (2011.01); G06F 18/214 (2023.01); G06T 3/06 (2024.01); G06T 7/11 (2017.01); G06T 17/00 (2006.01); G06V 10/26 (2022.01); G06V 10/762 (2022.01); G06V 20/10 (2022.01); G06V 20/64 (2022.01);
U.S. Cl.
CPC ...
G06T 17/05 (2013.01); G06F 18/2148 (2023.01); G06T 3/06 (2024.01); G06T 7/11 (2017.01); G06T 17/00 (2013.01); G06V 10/26 (2022.01); G06V 10/762 (2022.01); G06V 20/176 (2022.01); G06V 20/64 (2022.01); G06T 2200/08 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30184 (2013.01); G06T 2210/56 (2013.01);
Abstract

In an aspect for generating a 2-dimensional (2D) building mapping, a computer-implemented method may include one or more processors configured for receiving scanning data in a first file format corresponding to 3-dimensional (3D) aerial Light Detection and Ranging (LiDaR) images. Further, the method may include transforming the first file format to a second file format and transmitting the scanning data to a building semantic segmentation component. Further, the computer-implemented method may include generating semantic segmentation data corresponding to building structures defined by point clusters; generating instance segmentation data corresponding to top surfaces of the building structures; generating building boundary data for each one of the point clusters based on one or more of the semantic segmentation data and the instance segmentation data; and processing the building boundary data to generate a 2D building mapping comprising refined boundary lines for each of the point clusters.


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