A method comprising: at a computing platform comprising at least one processor, memory, and a communication interface: receiving, via the communication interface, video of a damaged vehicle; performing image analysis of the video to determine one or more frames of the video that include a damaged portion of the vehicle, comprising: determining, based on the video, a first frame that includes an image of the damaged portion of the vehicle; determining, based on the first frame, one or more representative frames by filtering the video to remove one or more non-representative frames of the video that do not include the damaged portion of the vehicle, wherein the one or more representative frames comprises the first frame; and determining, based on the one or more representative frames, one or more corresponding symmetrical frames for at least one of the one or more representative frames that each include an image of an undamaged portion of the vehicle, wherein the undamaged portion of the vehicle is substantially symmetrical to the damaged portion of the vehicle included in one of the one or more representative frames; further analyzing the one or more representative frames in relation to the one or more corresponding symmetrical frames of the video to determine a damaged cluster of parts of the vehicle; determining whether the damaged cluster of parts should be repaired or replaced; mapping the damaged cluster of parts to one or more parts in a vehicle-specific database of parts; and generating, based on the mapping, a list of parts for repair or replacement. receiving, via the communication interface, video of a damaged vehicle; performing image analysis of the video to determine one or more frames of the video that include a damaged portion of the vehicle, comprising: determining, based on the video, a first frame that includes an image of the damaged portion of the vehicle; determining, based on the first frame, one or more representative frames by filtering the video to remove one or more non-representative frames of the video that do not include the damaged portion of the vehicle, wherein the one or more representative frames comprises the first frame; and determining, based on the one or more representative frames, one or more corresponding symmetrical frames for at least one of the one or more representative frames that each include an image of an undamaged portion of the vehicle, wherein the undamaged portion of the vehicle is substantially symmetrical to the damaged portion of the vehicle included in one of the one or more representative frames; determining, based on the video, a first frame that includes an image of the damaged portion of the vehicle; determining, based on the first frame, one or more representative frames by filtering the video to remove one or more non-representative frames of the video that do not include the damaged portion of the vehicle, wherein the one or more representative frames comprises the first frame; and determining, based on the one or more representative frames, one or more corresponding symmetrical frames for at least one of the one or more representative frames that each include an image of an undamaged portion of the vehicle, wherein the undamaged portion of the vehicle is substantially symmetrical to the damaged portion of the vehicle included in one of the one or more representative frames; further analyzing the one or more representative frames in relation to the one or more corresponding symmetrical frames of the video to determine a damaged cluster of parts of the vehicle; determining whether the damaged cluster of parts should be repaired or replaced; mapping the damaged cluster of parts to one or more parts in a vehicle-specific database of parts; and generating, based on the mapping, a list of parts for repair or replacement. <EOS>