Augmented three dimensional point collection of vertical structures

1. An automated method, comprising:

receiving a first three-dimensional-data point cloud of a horizontal surface of an object of interest, the first three-dimensional-data point cloud having a first resolution and having a three-dimensional location associated with each point in the first three-dimensional-data point cloud;

receiving one or more aerial image, captured at one or more oblique angle, depicting at least a vertical surface of the object of interest, wherein the one or more aerial image comprises a first oblique aerial image having a first orientation in a first direction and a second oblique aerial image also having the first orientation in the first direction, and wherein the first oblique aerial image overlaps the second oblique aerial image;

determining three-dimensional locations of additional points on the object of interest by analyzing the one or more aerial image with a computer system; and

updating the first three-dimensional-data point cloud with the three-dimensional locations of the additional points on the object of interest to create a second three-dimensional-data point cloud having a second resolution greater than the first resolution of the first three-dimensional-data point cloud.

2. The automated method of claim 1 , further comprising discarding points in the second three-dimensional-data point cloud that are below a predetermined elevation based on the three-dimensional locations.

3. The automated method of claim 1 , wherein the one or more aerial image comprises, one or more aerial image captured with one or more the image capturing device mounted to a platform while flying the platform over a geographic area in which the object of interest is located.

4. The automated method of claim 3 , wherein the platform is unmanned.

5. The automated method of claim 3 , wherein the platform is manned.

6. The automated method of claim 1 , wherein receiving the first three-dimensional-data point cloud comprises receiving the first three-dimensional-data point cloud obtained with a LIDAR scanner system mounted to an airplane flying over a geographic area.

7. The automated method of claim 1 , further comprising forming a model of the object of interest from the second three-dimensional-data point cloud.

8. The automated method of claim 1 , wherein determining three-dimensional locations of additional points on the object of interest by analyzing the one or more aerial image with a computer system further comprises utilizing ray projection in analyzing the one or more aerial image.

9. The automated method of claim 1 , further comprising

classifying the points in the first three-dimensional-data point cloud into three or more categories comprising points representing an object of interest in an objects-of-interest category, points representing a background structure into a background-structure category, and points representing a ground surface into a surface-point category.

10. The automated method of claim 9 , wherein classifying the points in the first three-dimensional-data point cloud into three categories or more categories utilizes an algorithm that looks for an increased number of points at a predetermined radius from a search point having unclassified points.

11. A computer system, comprising:

one or more computer processors; and

one or more non-transitory memory storing computer readable instructions that, when executed by the one or more computer processors, cause the one or more computer processors to perform the following:

receiving a first three-dimensional-data point cloud of a horizontal surface of an object of interest, the first three-dimensional-data point cloud having a first resolution and having a three-dimensional location associated with each point in the first three-dimensional-data point cloud;

receiving one or more aerial image, captured at one or more oblique angle by one or more image-capturing devices, depicting at least a vertical surface of the object of interest wherein the one or more aerial image comprises a first oblique aerial image having a first orientation in a first direction and a second oblique aerial image also having the first orientation in the first direction, and wherein the first oblique aerial image overlaps the second oblique aerial image; and

determining from the one or more aerial image three-dimensional locations of additional points on the object of interest; and

updating the first three-dimensional-data point cloud with the three-dimensional locations of the additional points on the object of interest to create a second three-dimensional-data point cloud having a second resolution greater than the first resolution of the first three-dimensional-data point cloud.

12. The computer system of claim 11 , wherein the computer readable instructions, when executed by the one or more computer processors, cause the computer system to further discarding points in the second three-dimensional-data point cloud that are below a predetermined elevation based on the three-dimensional locations.

13. The computer system of claim 11 , wherein the one or more aerial image are captured by the one or more image-capturing devices from a platform while flying the platform over a geographic area in which the object of interest is located.

14. The computer system of claim 13 , wherein the platform is unmanned.

15. The computer system of claim 13 , wherein the platform is manned.

16. The computer system of claim 11 , wherein the first three-dimensional-data point cloud is captured by a LIDAR scanner system.

17. The computer system of claim 11 , wherein the computer readable instructions, when executed by the one or more computer processors, cause the computer system further to form a model of the object of interest from the second three-dimensional-data point cloud.

18. The computer system of claim 11 , wherein determining from the one or more aerial image three-dimensional locations of additional points on the object of interest further comprises utilizing ray projection in determining the three-dimensional locations of the additional points from the one or more aerial image.

19. The computer system of claim 18 , wherein the computer readable instructions, when executed by the one or more computer processors, cause the computer system further to:

classify the points in the first three-dimensional-data point cloud into three or more categories comprising points representing an object of interest in an objects-of-interest category, points representing a background structure into a background-structure category, and points representing a ground surface into a surface-point category.

20. The computer system of claim 19 , wherein classifying the points in the first three-dimensional-data point cloud into three categories or more categories utilizes an algorithm that looks for an increased number of points at a predetermined radius from a search point having unclassified points.