Automatic assessment of damage and repair costs in vehicles

A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause a computing device to perform operations of:

• causing a displaying of an outline of a selected damaged part of a damaged vehicle to be captured with a camera of a client device;
• causing the camera of the client device to capture an image of the damaged vehicle based on the displaying of the outline of the selected damaged part;
• receiving, from the client device, the image of the damaged vehicle;
• aligning the image to an undamaged version of the damaged vehicle;
• segmenting the image into vehicle parts;
• and
• detecting damage to a set of parts of the damaged vehicle by comparing portions of each vehicle part in the image to corresponding portions of each vehicle part in the undamaged version of the damaged vehicle, wherein detecting damage to the set of parts includes:
• comparing at least one of edge distribution, texture comparison, and spatial correlation of portions of each vehicle part in the image to corresponding portions of each vehicle part in the undamaged version of the damaged vehicle;
• determining whether at least one of the edge distribution, the texture comparison, and the spatial correlation exceeds a respective threshold difference value, wherein damage is detected in a portion of a vehicle part in the image if at least one of the edge distribution, the texture comparison, and the spatial correlation exceed the respective threshold difference value;
• detecting a pose of the damaged vehicle in the image;
• and
• determining which external vehicle parts are damaged in the image;
• and
• calculating an estimated repair cost for the damaged vehicle based on which external vehicle parts are damaged based on accessing a parts database that includes repair costs.

A computing device, comprising:

• a processor;
• and
• a memory storing instructions that, when executed by the processor, cause the computing device to perform operations of:
• causing a displaying of an outline of a selected damaged part of a damaged vehicle to be captured with a camera of a client device;
• causing the camera of the client device to capture an image of the damaged vehicle based on the displaying of the outline of the selected damaged part;
• receiving, from the client device, the image of the damaged vehicle;
• aligning the image to an undamaged version of the damaged vehicle;
• segmenting the image into vehicle parts;
• and
• detecting damage to a set of parts of the damaged vehicle by comparing portions of each vehicle part in the image to corresponding portions of each vehicle part in the undamaged version of the damaged vehicle, wherein detecting damage to the set of parts includes:
• comparing at least one of edge distribution, texture comparison, and spatial correlation of portions of each vehicle part in the image to corresponding portions of each vehicle part in the undamaged version of the damaged vehicle;
• determining whether at least one of the edge distribution, the texture comparison, and the spatial correlation exceeds a respective threshold difference value, wherein damage is detected in a portion of a vehicle part in the image if at least one of the edge distribution, the texture comparison, and the spatial correlation exceed the respective threshold difference value;
• detecting a pose of the damaged vehicle in the image;
• and
• determining which external vehicle parts are damaged in the image;
• and
• calculating an estimated repair cost for the damaged vehicle based on which external vehicle parts are damaged based on accessing a parts database that includes repair costs.