AI 2D-to-3D Video Conversion Using NeRF for Shared Virtual Viewing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video game streaming technologies lack the ability to enhance player and spectator engagement through immersive 3D experiences, limiting the potential for increased revenue and interaction.
Innovation Solution
A system and method utilizing Neural Radiance Fields (NeRF) to convert 2D video streams into 3D, enabling the generation of immersive 3D virtual models with customizable content and interactive environments, allowing multiple users to engage in shared virtual experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 2D video streams are converted to 3D virtual environments using NeRF, then player and spectator engagement is enhanced through immersive experiences, but system complexity and computational resources increase
Solution Approach 1:
The patent introduces a server as an intermediary component that hosts the NeRF model and handles the conversion process from 2D video streams to 3D virtual environments. This mediator architecture allows client devices to access immersive 3D experiences without requiring complex computational resources locally, thus enhancing engagement capability while managing system complexity through centralized processing.
Solution Approach 2:
The patent replaces traditional mechanical 3D capture methods (multiple cameras, physical setups) with AI-based Neural Radiance Fields that can generate 3D virtual environments from standard 2D video streams. This substitution eliminates the need for complex physical 3D capture equipment while achieving immersive experiences through computational modeling and machine learning.
2Adaptability or versatility
If NeRF technology is used to generate 3D virtual models from 2D video frames, then immersive 3D experiences are created, but processing time and computational load increase
Solution Approach 1:
The patent implements a workflow where 2D video streams are pre-processed and fed into the NeRF model in advance to generate 3D virtual environments before user interaction. This preliminary action allows the system to prepare immersive content ahead of time, reducing real-time processing delays and enabling faster user access to 3D experiences.
Solution Approach 2:
The patent employs dynamic frame selection and processing strategies where the system adaptively determines which video frames to process based on scene changes and user viewing angles. This dynamic approach processes only necessary portions of the video stream, significantly reducing overall processing time while maintaining high-quality 3D virtual model generation.
3Adaptability or versatility
If multiple users engage in shared virtual experiences, then interaction and revenue opportunities increase, but network bandwidth and server load increase
Solution Approach 1:
The patent implements a master-copy architecture where a single authoritative 3D virtual environment is generated and maintained on the server, while multiple user clients receive optimized copies or views tailored to their specific perspectives and devices. This copying strategy allows multiple users to experience the same virtual environment simultaneously without requiring duplicate full-resolution data transmission, thus supporting multi-user interaction while managing network bandwidth consumption.
Data Source
AI summary
A system is disclosed for three-dimensional (3D) conversion of a video stream. The system includes an input processor configured to receive an input video stream that includes a first series of video frames. The system also includes a 3D virtual model generator configured to select video frames from the input video stream and generate a 3D virtual model for content depicted in the selected video frames. The system also includes a frame generator configured to generate a second series of video frames for an output video stream depicting content within the 3D virtual model at a specified frame rate. The system also includes an output processor configured to encode and transmit the output video stream to a client computing system.