Bryce E Porter

US Patent:

20220366646, Nov 17, 2022

Filed:

May 17, 2022

Appl. No.:

17/746506

Inventors:

- Jersey City NJ, US
Ryan Mark Justus - Lehi UT, US
Bryce Zachary Porter - Lehi UT, US
Francisco Rivas - Madrid, ES

Assignee:

Insurance Services Office, Inc. - Jersey City NJ

International Classification:

G06T 17/05
G06V 10/42
G06V 10/82
G06V 20/10
G06F 16/587
G06T 3/40

Abstract:

Computer vision systems and methods for determining structure features from point cloud data using neural networks are provided. The system obtains point cloud data of a structure or a property parcel having a structure present therein from a database. The system can preprocess the obtained point cloud data to generate another point cloud or 3D representation derived from the point cloud data by spatial cropping and/or transformation, down sampling, up sampling, and filtering. The system can also preprocess point features to generate and/or obtain any new features thereof. Then, the system extracts a structure and/or feature of the structure from the point cloud data utilizing one or more neural networks. The system determines at least one attribute of the extracted structure and/or feature of the structure utilizing the one or more neural networks.

US Patent:

20220327722, Oct 13, 2022

Filed:

Apr 8, 2022

Appl. No.:

17/716623

Inventors:

- Jersey City NJ, US
Bryce Zachary Porter - Lehi UT, US

Assignee:

Insurance Services Office, Inc. - Jersey City NJ

International Classification:

G06T 7/60
G06T 7/11

Abstract:

Computer vision systems and methods for determining roof shapes from imagery using segmentation networks are provided. The system obtains an image of a structure from an image database, and determines a flat roof structure ratio and a sloped roof structure ratio of the roof structure using a neural network. Based on segmentation processing by the neural network, the system determines a flat roof structure ratio and a sloped roof structure ratio based on a portion of the roof structure classified as being flat and a portion of the roof structure classified as being sloped. Then, the system determines a ratio of each shape type of the roof structure using a neural network. The system generates a roof structure shape report indicative of a predominant shape of the roof structure and ratios of each shape type of the roof structure.

US Patent:

20220229946, Jul 21, 2022

Filed:

Jan 20, 2022

Appl. No.:

17/580279

Inventors:

- Jersey City NJ, US
Antonio Godino Cobo - South Jordan UT, US
Bryce Zachary Porter - Lehi UT, US

Assignee:

Insurance Services Office, Inc. - Jersey City NJ

International Classification:

G06F 30/13

Abstract:

Systems and methods for roof area and slope estimation using a point set are provided. The system selects roof structure points having a high probability of being positioned on a top surface of a structure present in the region of interest point set. Then, the system determines a footprint of the structure associated with the selected roof structure points. The system determines a distribution of the slopes of the roof structure points and generates a slope distribution report indicative of prominent slopes of the roof structure and each slope's contribution toward (percentage composition of) the total roof structure. The system then determines an area of the roof structure based on the footprint of the structure and the slope distribution report.

US Patent:

20220215645, Jul 7, 2022

Filed:

Jan 5, 2022

Appl. No.:

17/569077

Inventors:

- Jersey City NJ, US
Jose David Aguilera - South Jordan UT, US
Bryce Zachary Porter - Lehi UT, US
Francisco Rivas - Móstoles, ES

Assignee:

Insurance Services Office, Inc. - Jersey City NJ

International Classification:

G06V 10/26
G06V 10/25
G06V 10/82
G06T 7/11
G06T 7/12

Abstract:

Computer vision systems and methods for determining roof conditions from imagery using segmentation networks are provided. The system obtains at least one image from an image database having a roof structure present therein, and determines a footprint of the roof structure using a neural network. Based on segmentation processing by the neural network, the system generates a single channel image that maps each pixel in the at least one image to a binary classification indicative of whether each pixel is or is not representative of a roof structure and executes a contour extraction algorithm on the single channel image to determine the footprint of the roof structure. Then, the system determines condition features of the roof structure using the neural network, defines roof structure condition features, detects the roof structure condition features via segmentation, and generates a single channel image that maps each pixel in the obtained image to a condition label indicative of a defined roof structure condition feature. A roof structure condition feature report indicative of condition features of the roof structure and their respective contributions toward the total roof structure can be generated.

US Patent:

20210407188, Dec 30, 2021

Filed:

Aug 16, 2021

Appl. No.:

17/403792

Inventors:

- Jersey City NJ, US
Bryce Zachary Porter - Lehi UT, US
Ryan Mark Justus - Lehi UT, US
Francisco Rivas - Madrid, ES

Assignee:

Insurance Services Office, Inc. - Jersey City NJ

International Classification:

G06T 17/05
G06T 7/593
G06T 17/20
G06T 15/06
G06T 15/04
G06F 16/587

Abstract:

A system for modeling a roof structure comprising an aerial imagery database and a processor in communication with the aerial imagery database. The aerial imagery database stores a plurality of stereoscopic image pairs and the processor selects at least one stereoscopic image pair among the plurality of stereoscopic image pairs and related metadata from the aerial imagery database based on a geospatial region of interest. The processor identifies a target image and a reference image from the at least one stereoscopic pair and calculates a disparity value for each pixel of the identified target image to generate a disparity map. The processor generates a three dimensional point cloud based on the disparity map, the identified target image and the identified reference image. The processor optionally generates a texture map indicative of a three-dimensional representation of the roof structure based on the generated three dimensional point cloud.

US Patent:

20210158615, May 27, 2021

Filed:

Feb 2, 2021

Appl. No.:

17/165473

Inventors:

Bryce Zachary Porter - Lehi UT, US
Ryan Mark Justus - Lehi UT, US

International Classification:

G06T 17/10
G06T 15/10
G06N 3/08
G06F 30/13

Abstract:

A system for modeling a roof of a structure comprising a first database, a second database and a processor in communication with the first database and the second database. The processor selects one or more images and the respective metadata thereof from the first database based on a received a geospatial region of interest. The processor generates two-dimensional line segment geometries in pixel space based on two-dimensional outputs generated by a neural network in pixel space of at least one roof structure present in the selected one or more images. The processor classifies the generated two-dimensional line segment geometries into at least one contour graph based on three-dimensional data received from the second database and generates a three-dimensional representation of the at least one roof structure based on the at least one contour graph and the received three-dimensional data.

US Patent:

20190102897, Apr 4, 2019

Filed:

Nov 13, 2018

Appl. No.:

16/189339

Inventors:

- Lehi UT, US
Bryce Zachary Porter - Lehi UT, US
Ryan Mark Justus - Lehi UT, US

Assignee:

Xactware Solutions, Inc. - Lehi UT

International Classification:

G06T 7/564
G06T 7/12
G06F 17/30
G06T 7/536

Abstract:

A computer vision system and method for detecting and modeling features of a building in a plurality of images is provided. The system includes at least one computer system in communication with a database of aerial imagery, and computer vision system code executed by the at last one computer system which automatically detects contours and infers interior roof features of the building. The system first processes the plurality of images to identify a plurality of two-dimensional (2D) line segments in each image. Then, the system processes the plurality of 2D line segments to generate a plurality of three-dimensional (3D) line segments. The plurality of 2D line segments are then processed to detect a contour of the structure, and the contour of the structure is utilized by the system to infer interior roof lines from the structure. A model of the roof of the structure is finally generated using the detected contour and interior roof lines. The system can execute a straight-skeleton algorithm to infer the interior roof lines from the detected contour. Additionally, the system can detect roof rakes from the images.

US Patent:

20180089833, Mar 29, 2018

Filed:

Sep 27, 2016

Appl. No.:

15/277359

Inventors:

- Lehi UT, US
Bryce Zachary Porter - Lehi UT, US
Ryan Mark Justus - Lehi UT, US

Assignee:

Xactware Solutions, Inc. - Lehi UT

International Classification:

G06T 7/00
G06F 17/30

Abstract:

A computer vision system and method for detecting and modeling features of a building in a plurality of images is provided. The system includes at least one computer system in communication with a database of aerial imagery, and computer vision system code executed by the at last one computer system which automatically detects contours and infers interior roof features of the building. The system first processes the plurality of images to identify a plurality of two-dimensional (2D) line segments in each image. Then, the system processes the plurality of 2D line segments to generate a plurality of three-dimensional (3D) line segments. The plurality of 2D line segments are then processed to detect a contour of the structure, and the contour of the structure is utilized by the system to infer interior roof lines from the structure. A model of the roof of the structure is finally generated using the detected contour and interior roof lines. The system can execute a straight-skeleton algorithm to infer the interior roof lines from the detected contour. Additionally, the system can detect roof rakes from the images.