Three dimensional image scan for vehicle

• US 9,824,453 B1
• Filed: 10/14/2015
• Issued: 11/21/2017
• Est. Priority Date: 10/14/2015
• Status: Active Grant

• Current Assignee: Allstate Insurance Company (Allstate Corporation)
• Original Assignee: Allstate Insurance Company (Allstate Corporation)
• Inventors: Collins, Stephen M., Kwan, Randolph
• Primary Examiner(s): Kassa, Yosef
• Application Number:
  US14/882,945
• Time in Patent Office: 769 Days
• Field of Search: 382103, 382104, 382154, 382171, 382209, 382278, 382291, 348118, 348139, 348143
• CPC Class Codes: G06F 16/5838 using colour
• CPC Class Codes: G06F 18/40 Software arrangements specially adapted for pattern recognition, e.g. user interfaces or toolboxes therefor
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06T 2207/10012 Stereo images
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/30248 Vehicle exterior or interior
• CPC Class Codes: G06T 7/344 involving models
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes
• CPC Class Codes: G06V 10/17 using hand-held instruments
• CPC Class Codes: G06V 10/945 User interactive design; Environments; Toolboxes
• CPC Class Codes: G06V 20/20 in augmented reality scenes
• CPC Class Codes: G06V 20/64 Three-dimensional objects
• CPC Class Codes: G06V 2201/12 Acquisition of 3D measurements of objects
• CPC Class Codes: H04N 13/111 Transformation of image signals corresponding to virtual viewpoints, e.g. spatial image interpolation
• CPC Class Codes: H04N 13/133 Equalising the characteristics of different image components, e.g. their average brightness or colour balance
• CPC Class Codes: H04N 13/189 Recording image signals; Reproducing recorded image signals

Abstract

Systems and methods provide for an automated system for generating one or more three dimensional (3D) images of a vehicle and/or a baseline image for that vehicle. The system may receive 3D images of a plurality of vehicles of a same type (e.g., same make, model, year, etc.) and generate a 3D image of a baseline vehicle for vehicles of that same type based on 3D images of the plurality of vehicles of the particular type. The system may use a 3D image of the baseline vehicle to determine a characteristic of another vehicle, such as a modification made to the vehicle, damage to the vehicle, cost to repair the vehicle or replace parts of the vehicle, a value of the vehicle, an insurance quote for the vehicle, etc. In some aspects, the 3D images may optionally comprise 3D point clouds, and 3D laser scanners may be used to capture 3D images of vehicles.

Claims

1. A method comprising:

receiving, by a processing server, a plurality of three-dimensional (3D) images each depicting one of a plurality of vehicles of a same type;

generating, by the processing server, a 3D image of a baseline vehicle based on the plurality of 3D images, wherein the 3D image of the baseline vehicle comprises at least one of an average of at least two of the plurality of 3D images, a median of at least two of the plurality of 3D images, or a mode of at least two of the plurality of 3D images, and wherein the 3D image of the baseline vehicle comprises a point cloud image of the baseline vehicle; and

responsive to determining that a vehicle is of the same type as the plurality of vehicles, using the 3D image of the baseline vehicle to determine a characteristic of the vehicle, wherein using the 3D image of the baseline vehicle to determine the characteristic of the vehicle comprises;

comparing a point cloud image of the vehicle to the point cloud image of the baseline vehicle; and

based on the comparing, determining at least one difference between a point in the point cloud image of the vehicle and a point in the point cloud image of the baseline vehicle.

2. The method of claim 1, further comprising:

receiving, by the processing server, a 3D image of the vehicle from a mobile device that comprises a 3D imaging device,

wherein using the 3D image of the baseline vehicle to determine the characteristic of the vehicle comprises comparing the 3D image of the vehicle to the 3D image of the baseline vehicle.

3. The method of claim 2, wherein the 3D imaging device comprises a 3D laser scanner.

4. The method of claim 1, wherein the same type of vehicle comprises a make, a model, and a year of the vehicle, and wherein determining that the vehicle is the same type as the plurality of vehicles comprises determining that the vehicle has the same make, model, and year as the baseline vehicle.

5. The method of claim 1, wherein generating the 3D image of the baseline vehicle comprises, for at least one of the plurality of 3D images:

determining, by the processing server, at least one outlier point in at least one of the plurality of 3D images; and

removing, by the processing server, the at least one outlier point,

wherein generating the 3D image of the baseline vehicle comprises generating the 3D image of the baseline vehicle based on one or more of the plurality of 3D images from which the at least one outlier point was removed.

6. The method of claim 1, wherein using the 3D image of the baseline vehicle to determine the characteristic of the vehicle comprises determining a modification made to the vehicle relative to the baseline vehicle.

7. The method of claim 1, wherein using the 3D image of the baseline vehicle to determine the characteristic of the vehicle comprises determining damage to the vehicle relative to the baseline vehicle.

8. The method of claim 7, further comprising:

based on the damage to the vehicle, determining a part of the vehicle needing repair or replacement and a cost to repair or replace the part.

9. The method of claim 1, wherein using the 3D image of the baseline vehicle to determine the characteristic of the vehicle comprises determining a value of the vehicle based on a value of the baseline vehicle.

10. A system comprising:

a mobile device;

a 3D imaging device associated with the mobile device; and

a server comprising;

a processor; and

memory storing computer-executable instructions that, when executed by the processor, cause the server to;

receive a plurality of three-dimensional (3D) images each depicting one of a plurality of vehicles of a same type;

generate a 3D image of a baseline vehicle based on the plurality of 3D images, wherein the 3D image of the baseline vehicle comprises at least one of an average of at least two of the plurality of 3D images, a median of at least two of the plurality of 3D images, or a mode of at least two of the plurality of 3D images, and wherein the 3D image of the baseline vehicle comprises a point cloud image of the baseline vehicle;

receive a 3D image of a vehicle from the mobile device, wherein the 3D image of the vehicle is captured by the 3D imaging device; and

responsive to determining that a vehicle is of the same type as the plurality of vehicles, use the 3D image of the baseline vehicle to determine a characteristic of the vehicle, wherein using the 3D image of the baseline vehicle to determine the characteristic of the vehicle comprises;

comparing a point cloud image of the vehicle to the point cloud image of the baseline vehicle; and

based on the comparing, determining at least one difference between a point in the point cloud image of the vehicle and a point in the point cloud image of the baseline vehicle.

11. The system of claim 10, wherein generating the 3D image of the baseline vehicle comprises, for at least one of the plurality of 3D images:

determining at least one outlier point in at least one of the plurality of 3D images; and

removing the at least one outlier point,

wherein generating the 3D image of the baseline vehicle comprises generating the 3D image of the baseline vehicle based on one or more of the plurality of 3D images from which the at least one outlier point was removed.

12. The system of claim 10, wherein using the 3D image of the baseline vehicle to determine the characteristic of the vehicle comprises determining a modification made to the vehicle relative to the baseline vehicle.

13. The system of claim 10, wherein using the 3D image of the baseline vehicle to determine the characteristic of the vehicle comprises determining damage to the vehicle relative to the baseline vehicle.

14. The system of claim 13, wherein the memory stores computer-executable instructions that, when executed by the processor, cause the server to:

based on the damage to the vehicle, determine a part of the vehicle needing repair or replacement and a cost to repair or replace the part.

15. A non-transitory computer-readable media storing computer-readable instructions that, when executed by a computing device, cause the computing device to:

receive a plurality of three-dimensional (3D) images each depicting one of a plurality of vehicles of a same type;

generate a 3D image of a baseline vehicle based on the plurality of 3D images, wherein the 3D image of the baseline vehicle comprises at least one of an average of at least two of the plurality of 3D images, a median of at least two of the plurality of 3D images, or a mode of at least two of the plurality of 3D images, wherein the 3D image of the baseline vehicle comprises a point cloud image of the baseline vehicle; and

responsive to determining that a vehicle is of the same type as the plurality of vehicles, use the 3D image of the baseline vehicle to determine a characteristic of the vehicle, wherein using the 3D image of the baseline vehicle to determine the characteristic of the vehicle comprises;

comparing a point cloud image of the vehicle to the point cloud image of the baseline vehicle; and

based on the comparing, determining at least one difference between a point in the point cloud image of the vehicle and a point in the point cloud image of the baseline vehicle.

16. The non-transitory computer-readable media of claim 15, storing computer-readable instructions that, when executed by the computing device, cause the computing device to:

receive a 3D image of the vehicle from a mobile device that comprises a 3D imaging device,

wherein using the 3D image of the baseline vehicle to determine the characteristic of the vehicle comprises comparing the 3D image of the vehicle to the 3D image of the baseline vehicle.

17. The non-transitory computer-readable media of claim 15, wherein generating the 3D image of the baseline vehicle comprises, for at least one of the plurality of 3D images:

determining at least one outlier point in at least one of the plurality of 3D images; and

removing the at least one outlier point,

wherein generating the 3D image of the baseline vehicle comprises generating the 3D image of the baseline vehicle based on one or more of the plurality of 3D images from which the at least one outlier point was removed.