UTILIZING A 3D SCANNER TO ESTIMATE DAMAGE TO A ROOF
A damage assessment module operating on a computer system automatically evaluates a roof, estimating damage to the roof by analyzing a point cloud of a roof. The damage assessment module identifies individual shingles from the point cloud and detects potentially damaged areas on each of the shingles. The damage assessment module then maps the potentially damaged areas of each shingle back to the point cloud to determine which areas of the roof are damaged. Based on the estimation, the damage assessment module generates a report on the roof damage.
1 . A method, comprising:
generating an aggregate point cloud from two or more point clouds;
selecting a set of points by sampling the aggregate point cloud;
determining a threshold based on a distance for the set of points;
determining a potentially damaged object associated with a point cloud based on a comparison between points in the point cloud, the sampled set of points associated with the aggregate point cloud, and the threshold; and
displaying a report indicating at least the potentially damaged object associated with the point cloud.
2 . The method of claim 1 , wherein the distance is a mean nearest-neighbor distance.
3 . The method of claim 1 , wherein sampling the aggregate point cloud includes utilizing a voxel grid to down sample the set of points.
4 . The method of claim 3 , wherein the voxel grid creates boxes of a specified width and all points that lie inside a box are reduced down to their centroid.
5 . The method of claim 1 , wherein the threshold is a scaled number of standard deviations away from a mean.
6 . The method of claim 1 , wherein the aggregate point cloud corresponds to a plurality of shingles.
7 . The method of claim 1 , further comprising generating the two or more point clouds corresponding to two or more shingles.
8 . The method of claim 1 , further comprising aligning the two or more point clouds along one or more reference points.
9 . The method of claim 8 , wherein the one or more reference points include a center point associated with each of the two or more point clouds.
10 . A system, comprising:
a processor configured to:
generate an aggregate point cloud from two or more point clouds;
select a set of points by sampling the aggregate point cloud;
determine a threshold based on a distance for the set of points;
determine a potentially damaged object associated with a point cloud based on a comparison between points in the point cloud, the sampled set of points associated with the aggregate point cloud, and the threshold; and
display a report indicating at least the potentially damaged object associated with the point cloud; and
a memory coupled to the processor and configured to provide the processor with instructions.
11 . The system of claim 10 , wherein the distance is a mean nearest-neighbor distance.
12 . The system of claim 10 , wherein sampling the aggregate point cloud includes utilizing a voxel grid to down sample the set of points.
13 . The system of claim 10 , wherein the threshold is a scaled number of standard deviations away from a mean.
14 . The system of claim 10 , wherein the aggregate point cloud corresponds to a plurality of shingles.
15 . The system of claim 10 , wherein the processor is configured to generate the two or more point clouds corresponding to two or more shingles.
16 . A computer program product embodied in a non-transitory computer readable medium and comprising computer instructions for:
generating an aggregate point cloud from two or more point clouds;
selecting a set of points by sampling the aggregate point cloud;
determining a threshold based on a distance for the set of points;
determining a potentially damaged object associated with a point cloud based on a comparison between points in the point cloud, the sampled set of points associated with the aggregate point cloud, and the threshold; and
displaying a report indicating at least the potentially damaged object associated with the point cloud.
17 . The computer program product of claim 16 , wherein the distance is a mean nearest-neighbor distance, wherein sampling the aggregate point cloud includes utilizing a voxel grid to down sample the set of points.
18 . The computer program product of claim 16 , wherein the threshold is a scaled number of standard deviations away from a mean.
19 . The computer program product of claim 16 , wherein the aggregate point cloud corresponds to a plurality of shingles.
20 . The computer program product of claim 16 , further comprising generating the two or more point clouds corresponding to two or more shingles.