IP Library Granted Patent US 12,380,156
Granted Patent B2
US 12,380,156 · App. 18/734,841 · Granted Aug 5, 2025

Methods and systems for automatically classifying reality capture data

Inventors: Jay Nicholas Jackson (Noblesville, IN); Cody James Cahoon (Cary, NC)
Assignee: DroneDeploy, Inc.
G06F16/45
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Quick Facts
Patent No.
US 12,380,156
App. No.
18/734,841
Granted
Aug 5, 2025
Kind
B2
Abstract

A method for classifying a set of source files of reality capture data into an asset class of digital reality capture assets may include receiving, from a user device, a set of payloads including metadata of the set of source files of the reality capture data corresponding to a region of interest captured by a camera. The method may include classifying the set of source files of the reality capture data into the asset class of the digital reality capture assets, based on the set of payloads including the metadata of the set of source files of the reality capture data. The method may include providing, to the user device, information identifying the asset class of the digital reality capture assets to which the set of source files are classified to permit a digital reality capture asset, corresponding to the asset class, of the region of interest to be generated based on the set of source files.

Claims (34)

1. A method comprising:

receiving, by a user device, a set of source files of reality capture data corresponding to a region of interest captured by a camera;

generating, by the user device, a set of payloads including metadata of the set of source files;

providing, by the user device and to a server, the set of payloads to permit the server to classify the set of source files of the reality capture data into an asset class that identifies a type of digital reality capture asset to be generated based on the set of source files;

receiving, by the user device and from the server, information identifying the asset class of the digital reality capture assets to which the set of source files are classified to permit a digital reality capture asset, corresponding to the asset class, of the region of interest to be generated based on the set of source files; and

automatically updating, by the user device, the source files to include the information identifying the asset class of the digital reality capture assets to which the set of source files are classified.

2. The method of claim 1 , wherein the set of payloads includes less data than the set of source files.

3. The method of claim 1 , wherein the set of source files are generated by the camera of an unmanned aerial vehicle (UAV).

4. The method of claim 1 , wherein the server is configured to cluster the set of payloads into a cluster based on the metadata.

5. The method of claim 1 , wherein the metadata includes at least one of a latitude, a longitude, an altitude, a time stamp, an identifier of a camera, an identifier of an unmanned aerial vehicle, an identifier of a vehicle, a number of pixels, a pixel height, a pixel width, an aspect ratio, a file type, a flight identifier, a job identifier, a region of interest identifier, an entity identifier, an operator identifier, a user identifier, or a customer identifier.

6. The method of claim 1 , wherein the asset class includes a panorama, a walkthrough, a progress photo, a progress video, a raw file, a pre-processed panorama, an orthomosaic, a thermal capture, a multi-spectral image, a slant range image, or a façade capture.

7. A user device comprising:

a memory configured to store instructions; and

one or more processors configured to execute the instructions to perform operations comprising:

receiving a set of source files of reality capture data corresponding to a region of interest captured by a camera;

generating a set of payloads including metadata of the set of source files;

providing, to a server, the set of payloads to permit the server to classify the set of source files of the reality capture data into an asset class that identifies a type of digital reality capture asset to be generated based on the set of source files;

receiving, from the server, information identifying the asset class of the digital reality capture assets to which the set of source files are classified to permit a digital reality capture asset, corresponding to the asset class, of the region of interest to be generated based on the set of source files; and

automatically updating the source files to include the information identifying the asset class of the digital reality capture assets to which the set of source files are classified.

8. The user device of claim 7 , wherein the set of payloads includes less data than the set of source files.

9. The user device of claim 7 , wherein the set of source files are generated by the camera of an unmanned aerial vehicle (UAV).

10. The user device of claim 7 , wherein the server is configured to cluster the set of payloads into a cluster based on the metadata.

11. The user device of claim 7 , wherein the metadata includes at least one of a latitude, a longitude, an altitude, a time stamp, an identifier of a camera, an identifier of an unmanned aerial vehicle, an identifier of a vehicle, a number of pixels, a pixel height, a pixel width, an aspect ratio, a file type, a flight identifier, a job identifier, a region of interest identifier, an entity identifier, an operator identifier, a user identifier, or a customer identifier.

12. The user device of claim 7 , wherein the asset class includes a panorama, a walkthrough, a progress photo, a progress video, a raw file, a pre-processed panorama, an orthomosaic, a thermal capture, a multi-spectral image, a slant range image, or a façade capture.

13. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a user device, cause the one or more processors to perform operations comprising:

receiving a set of source files of reality capture data corresponding to a region of interest captured by a camera;

generating a set of payloads including metadata of the set of source files;

providing, to a server, the set of payloads to permit the server to classify the set of source files of the reality capture data into an asset class that identifies a type of digital reality capture asset to be generated based on the set of source files; and

receiving, from the server, information identifying the asset class of the digital reality capture assets to which the set of source files are classified to permit a digital reality capture asset, corresponding to the asset class, of the region of interest to be generated based on the set of source files; and

automatically updating the source files to include the information identifying the asset class of the digital reality capture assets to which the set of source files are classified.

14. The non-transitory computer-readable medium of claim 13 , wherein the set of payloads includes less data than the set of source files.

15. The non-transitory computer-readable medium of claim 13 , wherein the set of source files are generated by the camera of an unmanned aerial vehicle (UAV).

16. The non-transitory computer-readable medium of claim 13 , wherein the server is configured to cluster the set of payloads into a cluster based on the metadata.

17. The non-transitory computer-readable medium of claim 13 , wherein the metadata includes at least one of a latitude, a longitude, an altitude, a time stamp, an identifier of a camera, an identifier of an unmanned aerial vehicle, an identifier of a vehicle, a number of pixels, a pixel height, a pixel width, an aspect ratio, a file type, a flight identifier, a job identifier, a region of interest identifier, an entity identifier, an operator identifier, a user identifier, or a customer identifier.

Assignments (2)
SECURITY INTEREST Recorded Sep 3, 2025
From: DRONEDEPLOY, INC.; STRUCTIONSITE, INC.
To: HERCULES CAPITAL, INC., AS AGENT
Reel/Frame 072147/0547 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 10, 2025
From: JACKSON, JAY NICHOLAS; CAHOON, CODY JAMES
To: DRONEDEPLOY, INC
Reel/Frame 071375/0856 →
Continuity (2)
Continuation 17869233 · Jul 20, 2022
Related Publication 20240320260A1 · Sep 26, 2024
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