IP Library Granted Patent US 12,538,039
Granted Patent B2
US 12,538,039 · App. 18/620,829 · Granted Jan 27, 2026

Systems and methods for gate-based vehicle image capture

Inventors: Theobolt N. Leung (San Francisco, CA); Vinay Kumar (Fremont, CA); Holger Struppek (San Francisco, CA); Scott Howard (Emeryville, CA); Kenneth J. Sanchez (San Francisco, CA); John Minichiello (Normal, IL)
Assignee: QUANATA, LLC
H04N23/90G06Q40/08G06T7/0002G03B17/561G06T2207/30252H04N23/555
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,538,039
App. No.
18/620,829
Granted
Jan 27, 2026
Kind
B2
Abstract

A gate-based vehicle image capture system for analyzing vehicle image data is presented. The system may include a portable imaging gate apparatus configured to capture vehicle image data of a vehicle. The portable imaging gate apparatus may include a plurality of imaging assemblies positioned at a plurality of viewing angles. The system may further include an external processing server configured to receive the vehicle image data from the portable imaging gate apparatus. The external processing server may also analyze the vehicle image data to identify a plurality of vehicle features, and determine a first vehicle feature from the plurality of vehicle features. The first vehicle feature may be related to a vehicle incident. The system may also include a provider server configured to receive the first vehicle feature from the external processing server, and update an aspect of a risk evaluation based on the first vehicle feature.

Claims (44)

1 . A vehicle image analysis apparatus comprising:

one or more processors configured to:

receive vehicle image data of a vehicle captured by a portable imaging gate apparatus, wherein the portable imaging gate apparatus includes a plurality of imaging assemblies positioned at a plurality of viewing angles, and wherein each imaging assembly of the plurality of imaging assemblies includes one or more imaging devices and is configured to capture respective vehicle image data from a respective viewing angle of the plurality of viewing angles;

analyze the vehicle image data to identify one or more vehicle features;

determine a first vehicle feature from the one or more vehicle features; and

update a risk evaluation based at least on the first vehicle feature.

2 . The vehicle image analysis apparatus of claim 1 , wherein the plurality of viewing angles include one or more viewing angles featuring an undercarriage of the vehicle.

3 . The vehicle image analysis apparatus of claim 1 , wherein each imaging assembly of the plurality of imaging assemblies is adjustably connected to the portable imaging gate apparatus.

4 . The vehicle image analysis apparatus of claim 1 , wherein the one or more imaging devices are configured to capture the respective vehicle image data using at least one selected from a group consisting of visible light imaging, infrared imaging, and x-ray imaging.

5 . The vehicle image analysis apparatus of claim 1 , wherein the one or more processors are further configured to:

receive geolocation information of the portable imaging gate apparatus;

analyze the geolocation information to determine if the portable imaging gate apparatus is in one of one or more secure locations; and

determine the portable imaging gate apparatus is in one of the one or more secure locations.

6 . The vehicle image analysis apparatus of claim 1 , wherein an insurance policy is generated based on the risk evaluation, and updating the risk evaluation includes updating one or more of (i) a cost associated with the insurance policy, (ii) a premium associated with the insurance policy, (iii) a deductible associated with the insurance policy, (iv) a discount associated with the insurance policy, or (v) a coverage level associated with the insurance policy.

7 . A vehicle image data analysis method comprising:

receiving vehicle image data of a vehicle captured by a portable imaging gate apparatus, wherein the portable imaging gate apparatus includes a plurality of imaging assemblies positioned at a plurality of viewing angles, and wherein the portable imaging gate apparatus includes a plurality of imaging apparatuses, and each imaging apparatus of the plurality of imaging apparatuses includes one or more imaging devices and is configured to capture respective vehicle image data from a respective viewing angle of the plurality of viewing angles;

analyzing, by one or more processors, the vehicle image data to identify one or more vehicle features;

determining, by the one or more processors, a first vehicle feature from the one or more vehicle features;

updating, by the one or more processors, a risk evaluation based at least on the first vehicle feature; and

generating, by the one or more processors, an insurance policy based on the risk evaluation.

8 . The vehicle image data analysis method of claim 7 , wherein updating the risk evaluation includes updating one or more of (i) a cost associated with the insurance policy, (ii) a premium associated with the insurance policy, (iii) a deductible associated with the insurance policy, (iv) a discount associated with the insurance policy, or (v) a coverage level associated with the insurance policy.

9 . The vehicle image data analysis method of claim 7 , wherein the plurality of viewing angles include one or more viewing angles featuring an undercarriage of the vehicle.

10 . The vehicle image data analysis method of claim 7 , wherein each imaging apparatus of the plurality of imaging apparatuses is adjustably connected to the portable imaging gate apparatus.

11 . The vehicle image data analysis method of claim 9 , wherein the one or more imaging devices are configured to capture the respective vehicle image data using at least one selected from a group consisting of visible light imaging, infrared imaging, and x-ray imaging.

12 . The vehicle image data analysis method of claim 7 , wherein the vehicle image data is still image data or video data.

13 . The vehicle image data analysis method of claim 7 , further comprising:

receiving geolocation information of the portable imaging gate apparatus;

analyzing the geolocation information to determine if the portable imaging gate apparatus is in one of one or more secure locations; and

determining the portable imaging gate apparatus is in one of the one or more secure locations.

14 . A non-transitory computer readable storage medium comprising instructions stored thereon for analyzing vehicle image data, wherein the instructions when executed by one or more processors cause the one or more processors to:

receive the vehicle image data of a vehicle captured by a portable imaging gate apparatus, wherein the portable imaging gate apparatus includes a plurality of imaging assemblies positioned at a plurality of viewing angles, and wherein each imaging assembly of the plurality of imaging assemblies includes one or more imaging devices and is configured to capture respective vehicle image data from a respective viewing angle of the plurality of viewing angles;

analyze the vehicle image data to identify a plurality of vehicle features;

determine a first vehicle feature from the plurality of vehicle features, wherein the first vehicle feature is related to a vehicle incident; and

update a risk evaluation based at least on the first vehicle feature.

15 . The non-transitory computer readable storage medium of claim 14 , wherein the instructions when executed by the one or more processors further cause the one or more processors to:

generate an insurance policy based on the risk evaluation; and

update the risk evaluation by updating one or more of (i) a cost associated with the insurance policy, (ii) a premium associated with the insurance policy, (iii) a deductible associated with the insurance policy, (iv) a discount associated with the insurance policy, or (v) a coverage level associated with the insurance policy.

16 . The non-transitory computer readable storage medium of claim 14 , wherein the instructions when executed by the one or more processors further cause the one or more processors to:

receive geolocation information of the portable imaging gate apparatus;

analyze the geolocation information to determine if the portable imaging gate apparatus is in one of one or more secure locations; and

determine the portable imaging gate apparatus is in one of the one or more secure locations.

17 . The non-transitory computer readable storage medium of claim 14 , wherein the plurality of viewing angles include one or more viewing angles featuring an undercarriage of the vehicle.

18 . The non-transitory computer readable storage medium of claim 14 , wherein each imaging assembly of the plurality of imaging assemblies is adjustably connected to the portable imaging gate apparatus.

19 . The non-transitory computer readable storage medium of claim 14 , wherein the one or more imaging devices are configured to capture the respective vehicle image data using at least one selected from a group consisting of visible light imaging, infrared imaging, and x-ray imaging.

Assignments (2)
CHANGE OF NAME Recorded May 29, 2024
From: BLUEOWL, LLC
To: QUANATA, LLC
Reel/Frame 067558/0600 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 12, 2024
From: LEUNG, THEOBOLT N.; KUMAR, VINAY; STRUPPEK, HOLGER; HOWARD, SOCTT; SANCHEZ, KENNETH JASON; MINICHIELLO, JOHN
To: BLUEOWL, LLC
Reel/Frame 067088/0125 →
Continuity (3)
Continuation 17838870 · Jun 13, 2022
Continuation 16667759 · Oct 29, 2019
Related Publication 20240267640A1 · Aug 8, 2024
References Cited (92)
US 7813944B1 · Luk et al. · 2010 [cited by applicant]
US 8117049B2 · Berkobin et al. · 2012 [cited by applicant]
US 9047778B1 · Cazanas et al. · 2015 [cited by applicant]
US 9151692B2 · Breed · 2015 [cited by applicant]
US 9275417B2 · Binion et al. · 2016 [cited by applicant]
US 9299108B2 · Diana et al. · 2016 [cited by applicant]
US 9311676B2 · Helitzer et al. · 2016 [cited by applicant]
US 9679487B1 · Hayward · 2017 [cited by applicant]
US 9712549B2 · Almurayh · 2017 [cited by applicant]
US 9870448B1 · Myers et al. · 2018 [cited by applicant]
US 9904928B1 · Leise · 2018 [cited by applicant]
US 9984419B1 · Manzella et al. · 2018 [cited by applicant]
US 9984420B1 · Manzella et al. · 2018 [cited by applicant]
US 10026130B1 · Konrardy et al. · 2018 [cited by applicant]
US 10032225B1 · Fox et al. · 2018 [cited by applicant]
US 10042359B1 · Konrardy et al. · 2018 [cited by applicant]
US 10055794B1 · Konrardy et al. · 2018 [cited by applicant]
US 10086782B1 · Konrardy et al. · 2018 [cited by applicant]
US 10089693B1 · Konrardy et al. · 2018 [cited by applicant]
US 10102590B1 · Farnsworth et al. · 2018 [cited by applicant]
US 10106083B1 · Fields et al. · 2018 [cited by applicant]
US 10127737B1 · Manzella et al. · 2018 [cited by applicant]
US 10134278B1 · Konrardy et al. · 2018 [cited by applicant]
US 10156848B1 · Konrardy et al. · 2018 [cited by applicant]
US 10157423B1 · Fields et al. · 2018 [cited by applicant]
US 10163327B1 · Potter et al. · 2018 [cited by applicant]
US 10163350B1 · Fields et al. · 2018 [cited by applicant]
US 10166994B1 · Fields et al. · 2019 [cited by applicant]
US 10168703B1 · Konrardy et al. · 2019 [cited by applicant]
US 10181161B1 · Konrardy et al. · 2019 [cited by applicant]
US 10185997B1 · Konrardy et al. · 2019 [cited by applicant]
US 10185998B1 · Konrardy et al. · 2019 [cited by applicant]
US 10185999B1 · Konrardy et al. · 2019 [cited by applicant]
US 10210678B1 · Manzella et al. · 2019 [cited by applicant]
US 10269074B1 · Patel et al. · 2019 [cited by applicant]
US 10295363B1 · Konrardy et al. · 2019 [cited by applicant]
US 10354333B1 · Hayward · 2019 [cited by applicant]
US 10410289B1 · Tofte et al. · 2019 [cited by applicant]
US 10534968B1 · Clauss et al. · 2020 [cited by applicant]
US 10643287B1 · Manzella et al. · 2020 [cited by applicant]
US 10832327B1 · Potter et al. · 2020 [cited by applicant]
US 11216888B2 · Perl et al. · 2022 [cited by applicant]
US 11417208B1 · Leung et al. · 2022 [cited by applicant]
US 20030200123A1 · Burge et al. · 2003 [cited by applicant]
US 20040243423A1 · Rix et al. · 2004 [cited by applicant]
US 20080077451A1 · Anthony · 2008 [cited by examiner]
US 20080243558A1 · Gupte · 2008 [cited by applicant]
US 20100088123A1 · Mccall et al. · 2010 [cited by applicant]
US 20100145734A1 · Becerra et al. · 2010 [cited by applicant]
US 20120076437A1 · King · 2012 [cited by applicant]
US 20130166326A1 · Lavie · 2013 [cited by examiner]
US 20130317665A1 · Fernandes et al. · 2013 [cited by applicant]
US 20130317736A1 · Fernandes et al. · 2013 [cited by applicant]
US 20140081675A1 · Ives et al. · 2014 [cited by applicant]
US 20150025917A1 · Stempora · 2015 [cited by applicant]
US 20150039397A1 · Fuchs · 2015 [cited by applicant]
US 20150179062A1 · Ralston et al. · 2015 [cited by applicant]
US 20150204684A1 · Rostamian et al. · 2015 [cited by applicant]
US 20150363886A1 · Fernandes et al. · 2015 [cited by applicant]
US 20160001544A1 · Gydesen · 2016 [cited by applicant]
US 20170013228A1 · Kalendra · 2017 [cited by examiner]
US 20170075740A1 · Breaux et al. · 2017 [cited by applicant]
US 20170089710A1 · Slusar · 2017 [cited by applicant]
US 20170109827A1 · Huang et al. · 2017 [cited by applicant]
US 20170192428A1 · Vogt et al. · 2017 [cited by applicant]
US 20170200367A1 · Mielenz · 2017 [cited by applicant]
US 20170212511A1 · Paiva et al. · 2017 [cited by applicant]
US 20170270615A1 · Fernandes et al. · 2017 [cited by applicant]
US 20170270617A1 · Fernandes et al. · 2017 [cited by applicant]
US 20170293894A1 · Taliwal et al. · 2017 [cited by applicant]
US 20180070290A1 · Breaux et al. · 2018 [cited by applicant]
US 20180070291A1 · Breaux et al. · 2018 [cited by applicant]
US 20180182039A1 · Wang et al. · 2018 [cited by applicant]
US 20180194343A1 · Lorenz · 2018 [cited by applicant]
US 20180307250A1 · Harvey · 2018 [cited by applicant]
US 20190102840A1 · Perl et al. · 2019 [cited by applicant]
US 20210042844A1 · Potter et al. · 2021 [cited by applicant]
US 20210078629A1 · Boss et al. · 2021 [cited by applicant]
CN 103810637 · 2014 [cited by applicant]
WO 2017176304 · 2017 [cited by applicant]
Jiangqin Peng, Nanjie Lui, Haitao Zhao and Minglu Yu, “Usage-based insurance system based on carrier-cloud-client,” 2015 10th International Conference on Communication and Networking in China (ChinaCom), 2015 pp. 579-58… [cited by applicant]
<https://gilsmethod.com/how-to-create-albums-and-upload-pictures-to-facebook-on-your-iphone>. GilsMethod, Oct. 15, 2019. 2019. [cited by applicant]
<https://grytics.com/blog/create-album-facebook-groups/>. Grytics. Oct. 15, 2019. 2019. [cited by applicant]
<https://www.dummies.com/social-media/facebook/how-to-edit-a-facebook-album/>. Dummies. Oct. 15, 2019. 2019. [cited by applicant]
<https://www.socmedsean.com/updated-facebook-tip-organizing-moving-and-editing-your-photos-and-albums/. SocMedSean. Ocotober 15, 2019. 2019. [cited by applicant]
<https://www.thesocialmediahat.com/blog/how-to-update-your-new-mobile-facebook-profile/>. The Social Media Hat. Oct. 15, 2019. 2019. [cited by applicant]
Aleksandrowicz, P., Verification of motor vehicle post accident insurance claims. University of Science and Technology, Institute of Automation and Transport, Machine Maintenance Department, vol. 15, No. 1, 2020, pp. 25… [cited by applicant]
fidelity.com, “Mobile Check Deposit”, Deposit checks on the go. Just snap a photo of the check with your iPhone (Registered), iPad(Registered), or AndroidTM device to make deposits directly into the Fidelity account of … [cited by applicant]
leadtools.com, “Credit Card Recognition SOK Technology”, Copyright 2019 LEAD Technologies, Inc, pp. 1-2. Retrieved from the internet on Aug. 15, 2019: https://www.leadtools.com/sdk/forms/credit-card 2019. [cited by applicant]
Li et al., An Anti-Fraud System for Car Insurance Claim Based on Visual Evidence, retrieved from https://arxiv.org/pdf/1804.11207, Apr. 2018, 6 pages. 2018. [cited by applicant]
Ruchi Verma and Sathyan Ramakrishana Mani, “Using Analytics for Insurance Fraud Detection”, Digital Transformation, pp. 1-10. [cited by applicant]
truepic.com, “Photo and Video Verification You Can Trust”, 2019 World Economic Forum Tech Pioneer, pp. 1-4. Retrieved from the internet on Aug. 15, 2019: https://truepic.com/ 2019. [cited by applicant]