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US Patent 12002192 Transfer of damage markers from images to 3D vehicle models for damage assessment

Patent 12002192 was granted and assigned to Solera Holdings on June, 2024 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
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Patent attributes

Patent Applicant
Solera Holdings
Solera Holdings
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Current Assignee
Solera Holdings
Solera Holdings
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
120021920
Patent Inventor Names
Andrey Lutich0
Mihran Shahinian0
Date of Patent
June 4, 2024
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Patent Application Number
174550560
Date Filed
November 16, 2021
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Patent Citations
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US Patent 10373260 Imaging processing system for identifying parts for repairing a vehicle
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US Patent 10430886 Processing insured items holistically with mobile damage assessment and claims processing
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US Patent 10507550 Evaluation system for work region of vehicle body component and evaluation method for the work region
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US Patent 10825097 Systems and methods for utilizing machine-assisted vehicle inspection to identify insurance buildup or fraud
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US Patent 11043000 Measuring method and apparatus for damaged part of vehicle
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US Patent 11106926 Methods and systems for automatically predicting the repair costs of a damaged vehicle from images
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US Patent 11120574 Methods and systems for obtaining image data of a vehicle for automatic damage assessment
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US Patent 11144889 Automatic assessment of damage and repair costs in vehicles
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...
Patent Primary Examiner
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Michael S Osinski
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CPC Code
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G06V 2201/08
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G06T 7/0004
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G06T 7/10
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G06T 7/70
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G06T 17/00
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G06T 2200/24
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G06T 2207/20081
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G06T 2207/30204
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Patent abstract

A method includes obtaining an image of a damaged vehicle and a three-dimensional (3D) vehicle model associated with the damaged vehicle. The method also includes identifying one or more damage markers that indicate damage to the damaged vehicle based on the image. The method further includes identifying a pose of the damaged vehicle within the image. In addition, the method includes mapping the one or more damage markers onto the 3D vehicle model based on the identified pose, where the one or more mapped damage markers identify one or more locations and dimensions of the damage to the damaged vehicle on the 3D vehicle model. In some cases, one or more trained machine learning models may be used to identify the one or more damage markers, identify the pose of the damaged vehicle within the image, and/or map the one or more damage markers onto the 3D vehicle model.

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