Augmented three dimensional point collection of vertical structures

• US 9,542,738 B2
• Filed: 03/03/2016
• Issued: 01/10/2017
• Est. Priority Date: 01/31/2014
• Status: Active Grant

• Current Assignee: Pictometry International Corporation (EagleView Technologies Incorporated)
• Original Assignee: Pictometry International Corporation (EagleView Technologies Incorporated)
• Inventors: Schultz, Stephen L., Nilosek, David R., Petterson, David S., Harrington, Timothy S.
• Primary Examiner(s): Rahmjoo, Manuchehr
• Application Number:
  US15/060,264
• Publication Number:
  US 20160189367A1
• Time in Patent Office: 313 Days
• Field of Search: 382/190
• US Class Current: 1/1
• CPC Class Codes: G01C 11/04 Interpretation of pictures
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G01S 7/4808 Evaluating distance, position or velocity data
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/10032 Satellite or aerial image; Remote sensing
• CPC Class Codes: G06T 2207/10044 Radar image
• CPC Class Codes: G06T 2207/30184 Infrastructure
• CPC Class Codes: G06T 7/0004 Industrial image inspection
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06T 7/521 from laser ranging, e.g. using interferometry; from the projection of structured light
• CPC Class Codes: G06T 7/66 of image moments or centre of gravity
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06V 20/176 Urban or other man-made structures
• CPC Class Codes: G06V 30/422 Technical drawings; Geographical maps
• CPC Class Codes: H04N 13/10 Processing, recording or transmission of stereoscopic or multi-view image signals

Abstract

Automated methods and systems of creating three dimensional LIDAR data are disclosed, including a method comprising capturing images of a geographic area with one or more image capturing devices as well as location and orientation data for each of the images corresponding to the location and orientation of the one or more image capturing devices capturing the images, the images depicting an object of interest; capturing three-dimensional LIDAR data of the geographic area with one or more LIDAR system such that the three-dimensional LIDAR data includes the object of interest; storing the three-dimensional LIDAR data on a non-transitory computer readable medium; analyzing the images with a computer system to determine three dimensional locations of points on the object of interest; and updating the three-dimensional LIDAR data with the three dimensional locations of points on the object of interest determined by analyzing the images.

Claims

1. A method for analyzing a utility network comprising:

capturing images of a geographic area encompassing at least a portion of a utility network with one or more image capturing devices, the images including utility wires and utility towers having cross bars as well as location and orientation data for each of the images corresponding to the location and orientation of the one or more image capturing devices capturing the image; and

analyzing at least one of the images with a computer system running a utility network detection algorithm with a gabor filter to identify pixel locations within the at least one image of cross bars depicted within the images, wherein the gabor filter is a first gabor filter having a first longitudinal axis, the pixel locations are first pixel locations, and wherein analyzing further comprises analyzing at least one of the images with the computer system running the utility network detection algorithm with a second gabor filter having a second longitudinal axis substantially aligned with the utility wires depicted in the at least one image to identify second pixel locations within the at least one of the images of the utility wires depicted within the at least one of the images, wherein the first longitudinal axis extends within a range between 85 to 95 degrees relative to the second longitudinal axis.

2. The method of claim 1, further comprising the step of converting the first and second pixel locations to real-world three dimensional coordinates using the first and second pixel locations and the location and orientation data corresponding to the location and orientation of the one or more image capturing devices capturing the images and storing the real-world three dimensional coordinates within a three-dimensional model of the utility network.