US 12,248,505 B2
Automatic annotation for vehicle damage
Avid Ghamsari, Carrollton, TX (US); Qiaochu Tang, Frisco, TX (US); Geoffrey Dagley, McKinney, TX (US); and Micah Price, The Colony, TX (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Nov. 27, 2023, as Appl. No. 18/519,892.
Application 18/519,892 is a continuation of application No. 18/059,656, filed on Nov. 29, 2022, granted, now 11,868,388.
Application 18/059,656 is a continuation of application No. 17/089,881, filed on Nov. 5, 2020, granted, now 11,544,316, issued on Jan. 3, 2023.
Application 17/089,881 is a continuation of application No. 16/786,695, filed on Feb. 10, 2020, granted, now 10,846,322, issued on Nov. 24, 2020.
Prior Publication US 2024/0134900 A1, Apr. 25, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/41 (2019.01); G06F 16/45 (2019.01); G06F 16/48 (2019.01); G06F 18/2413 (2023.01); G06N 20/00 (2019.01); G06V 10/764 (2022.01)
CPC G06F 16/41 (2019.01) [G06F 16/45 (2019.01); G06F 16/48 (2019.01); G06F 18/2413 (2023.01); G06N 20/00 (2019.01); G06V 10/764 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving vehicle-specific identifying information corresponding to a vehicle;
determining, based on image data received from one or more image sensors and corresponding to one or more aspects of the vehicle, image data corresponding to the one or more aspects of the vehicle;
determining, using a machine learning model, one or more instances of damage to the one or more aspects;
determining, using the machine learning model, an extent of damage at each of the one or more instances of damage;
annotating, based on the one or more instances of damage, the image data corresponding to the one or more aspects to reflect the one or more instances of damage and the extent of damage at each of the one or more instances of damage;
generating, using the machine learning model, an interactive multimedia content associated with the vehicle, wherein the interactive multimedia content comprises the annotated image data indicating the one or more instances of damage and the extent of damage at each of the one or more instances of damage; and
causing, through a user interface and responsive to a request, display of the interactive multimedia content of the vehicle.