Systems and methods for pitch determination

Patent metadata

Field	Value
Publication number	US-2023215087-A1
Application number	US-202117445939-A
Country	US
Kind code	A1
Filing date	Aug 25, 2021
Priority date	Aug 26, 2020
Publication date	Jul 6, 2023
Grant date	—

Abstract

Systems and methods are provided for pitch determination. An example method includes obtaining an image depicting a structure, the image being captured via a user device positioned proximate to the structure. The image is segmented to identify, at least, a roof facet of the structure. An eave vector and a rake vector which are associated with the roof facet are determined. A normal vector of the roof facet is calculated based on the eave vector and the rake vector, and compared to a vector indicating a vertical direction such as gravity. The angle made out by the normal and a gravity vector may be utilized to calculate the pitch of the roof facet.

First claim

1 - 14 . (canceled)

15 . A method implemented by a system of one or more computers, the method comprising:
obtaining an image depicting a structure, the image being captured via a user device positioned proximate to the structure, the structure having a plurality of planar elements; providing the image as input to a neural network, wherein a forward pass through the neural network is computed, and wherein the neural network outputs, at least, a surface normal associated with a roof facet depicted in the image, and wherein the neural network is trained to output a surface normal associated with at least one of the plurality of planar elements of the structure; and adjusting an orientation of the structure by aligning at least one of the plurality of planar elements of the structure to a vertical orientation.

16 . The method of claim 15 , wherein the neural network comprises a convolutional neural network trained to assign at least one of the planar elements as a roof facet.

17 . The method of claim 16 , wherein the neural network further comprises one or more fully-connected layers which receive output from the convolutional neural network, and wherein the fully-connected layers are trained to output the surface normal.

18 . The method of claim 15 , wherein the neural network is trained to determine surface normal for a plurality of planar elements of the structure, and wherein the system identifies a roof facet from the plurality of portions.

19 . (canceled)

20 . The method of claim 15 , wherein the system is configured to determine a plurality of surface normals corresponding to a plurality of roof facets.

21 . The method of claim 15 , wherein the image was captured below a maximum height of the structure.

22 . The method of claim 15 , wherein a pitch of the roof facet is determined based on the surface normal and a gravity vector.

23 . A system comprising one or more processors and non-transitory computer-readable media storing instructions which, when executed by the one or more processors, cause the one or more processors to perform the method of claims 15 - 22 .

24 - 34 . (canceled)

Assignees

• Hover Inc

Inventors

• Castillo William
• Murali Giridhar
• Scott Brandon
• Jia Kai
• Sommers Jeffrey
• Rethage Dario

Classifications

• G06T7/10

  Segmentation; Edge detection (motion-based segmentation G06T7/215) · CPC title

• G06N3/08

  Learning methods · CPC title

• G06T17/00 Primary

  Three-dimensional [3D] modelling for computer graphics · CPC title

• G06T7/70

  Determining position or orientation of objects or cameras (camera calibration G06T7/80) · CPC title

• G06T2207/20092

  Interactive image processing based on input by user · CPC title