IP Library Granted Patent US 12682575
Granted Patent B2
US 12682575 · App. 18/772,233 · Granted Jul 14, 2026

Virtual environment-based obstacle manipulation

Inventors: Sarbajit Kumar Rakshit (Kolkata, IN); Sathya Santhar (Chennai, IN); Sridevi Kannan (Chennai, IN)
Assignee: International Business Machines Corporation
G06T19/00G06F3/013G06F3/017
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Quick Facts
Patent No.
US 12682575
App. No.
18/772,233
Granted
Jul 14, 2026
Kind
B2
Abstract

Techniques are described with respect to a system, method, and computer program product for virtual environment-based obstacle manipulation. An associated method includes receiving a stream of media data associated with a virtual environment; analyzing a plurality of sensor data associated with a user of the virtual environment; detecting one or more obstacles associated with the virtual environment; and optimizing the stream of media data, the optimizing comprising manipulation of the one or more obstacles based on the analysis of the plurality of sensor data.

Claims (50)

1 . A computer-implemented method for virtual environment-based obstacle manipulation, the method comprising:

receiving, by a computing device, a stream of media data associated with a virtual environment;

analyzing, by the computing device, a plurality of sensor data associated with a user of the virtual environment;

detecting, by the computing device, one or more obstacles associated with the virtual environment; and

optimizing, by the computing device, the stream of media data, the optimizing comprising utilizing a three-dimensional (3D) reconstruction model of the virtual environment configured to be processed by a generative model and manipulation of the one or more obstacles based on the analysis of the plurality of sensor data.

2 . The computer-implemented method of claim 1 , wherein the one or more obstacles are inhibiting at least a view of the user within the virtual environment.

3 . The computer-implemented method of claim 1 , wherein analysis of the sensor data derives one or more of gaze detection, gesture analysis, linguistic input analysis, or combination thereof.

4 . The computer-implemented method of claim 1 , wherein optimizing the stream of media data comprises:

receiving, by the computing device, a user input configured to direct a manipulation of the one or more obstacles;

wherein the manipulation comprises removal or modifying the one or more obstacles based on the user input within the virtual environment.

5 . The computer-implemented method of claim 1 , wherein optimizing the stream of media data comprises:

identifying, by the computing device, a plurality of latent spaces of the virtual environment based on one or more outputs of a machine learning model.

6 . The computer-implemented method of claim 5 , wherein utilizing the 3D reconstruction model comprises:

utilizing, by the computing device, the generative model to perform an analysis of a plurality of virtual element data associated with the virtual environment.

7 . The computer-implemented method of claim 5 , wherein utilizing the 3D reconstruction model comprises:

synthesizing, by the computing device, optimized stream media data generated by the generative model configured to be integrated into the virtual environment.

8 . A computer program product for virtual environment-based obstacle manipulation, the computer program product comprising or more computer readable storage media and program instructions collectively stored on the one or more computer readable storage media, the stored program instructions comprising:

program instructions to receive a stream of media data associated with a virtual environment;

program instructions to analyze a plurality of sensor data associated with a user of the virtual environment;

program instructions to detect one or more obstacles associated with the virtual environment; and

program instructions to optimize the stream of media data, program instructions to optimize further comprising program instructions to utilize a three-dimensional (3D) reconstruction model of the virtual environment configured to be processed by a generative model and manipulate the one or more obstacles based on the analysis of the plurality of sensor data.

9 . The computer program product of claim 8 , wherein the one or more obstacles are inhibiting at least a view of the user within the virtual environment.

10 . The computer program product of claim 8 , wherein analysis of the sensor data derives one or more of gaze detection, gesture analysis, linguistic input analysis, or combination thereof.

11 . The computer program product of claim 8 , wherein the program instructions to optimize the stream of media data further comprise:

program instructions to receive a user input configured to direct a manipulation of the one or more obstacles;

wherein the manipulation comprises program instructions to remove or modify the one or more obstacles based on the user input within the virtual environment.

12 . The computer program product of claim 8 , wherein the program instructions to optimize the stream of media data further comprise:

program instructions to identify a plurality of latent spaces of the virtual environment based on one or more outputs of a machine learning model.

13 . The computer program product of claim 12 , wherein the program instructions to utilize the 3D reconstruction model comprise:

program instructions to utilize the generative model to perform an analysis of a plurality of virtual element data associated with the virtual environment.

14 . The computer program product of claim 12 , wherein the program instructions to utilize the 3D reconstruction model comprise:

program instructions to synthesize the optimized stream media data generated by the generative model configured to be integrated into the virtual environment.

15 . A computer system for virtual environment-based obstacle manipulation, the computer system comprising:

one or more processors;

one or more computer-readable memories;

program instructions stored on at least one of the one or more computer-readable memories for execution by at least one of the one or more processors, the program instructions comprising:

program instructions to receive a stream of media data associated with a virtual environment;

program instructions to analyze a plurality of sensor data associated with a user of the virtual environment;

program instructions to detect one or more obstacles associated with the virtual environment; and

program instructions to optimize the stream of media data, program instructions to optimize further comprising program instructions to utilize a three-dimensional (3D) reconstruction model of the virtual environment configured to be processed by a generative model and manipulate the one or more obstacles based on the analysis of the plurality of sensor data.

16 . The computer system of claim 15 , wherein the one or more obstacles are inhibiting at least a view of the user within the virtual environment.

17 . The computer system of claim 15 , wherein the program instructions to optimize the stream of media data further comprise:

program instructions to receive a user input configured to direct a manipulation of the one or more obstacles;

wherein the manipulation comprises program instructions to remove or modify the one or more obstacles based on the user input within the virtual environment.

18 . The computer system of claim 15 , wherein the program instructions to optimize the stream of media data further comprise:

program instructions to identify a plurality of latent spaces of the virtual environment based on one or more outputs of a machine learning model.

19 . The computer system of claim 18 , wherein the program instructions to utilize the 3D reconstruction model comprise:

program instructions to utilize the generative model to perform an analysis of a plurality of virtual element data associated with the virtual environment.

20 . The computer system of claim 15 , wherein the program instructions to utilize the 3D reconstruction model comprise:

program instructions to synthesize the optimized stream media data generated by the generative model configured to be integrated into the virtual environment.