Interactive 3D Media Galleries From Gaming Session Capture
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Solution Overview
Problem
Current gaming media galleries only support the capture, view, and sharing of 2D screenshots and videos, lacking the ability to generate and share interactive 3D content, which limits user engagement and creativity.
Innovation Solution
A framework for capturing, generating, and sharing interactive 3D content from gaming sessions using point-based representations like Gaussian splats or implicit representations like Neural Radiance Fields, enabling 3D content interaction and sharing across various devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 2D content capture and sharing is implemented in media galleries, then basic media management functionality is achieved, but user engagement and creativity are limited
Solution Approach 1:
The patent transforms 2D captured content into 3D interactive models by extracting multiple 2D frames from different angles and synthesizing them into three-dimensional representations. This dimensionality change enables users to interact with content from multiple perspectives, significantly enhancing engagement while maintaining manageable processing complexity through efficient frame extraction and 3D synthesis algorithms.
Solution Approach 2:
The patent introduces an intermediary processing system that captures 2D content, extracts frames, generates 3D models, and prepares them for sharing. This intermediary layer handles the complex processing tasks, allowing the media gallery interface to remain simple while enabling advanced 3D interaction capabilities through the intermediate 3D model generation step.
2Adaptability or versatility
If 3D content generation from 2D content is implemented, then interactive content capability is improved, but processing complexity increases
Solution Approach 1:
The patent segments the 3D content generation process into distinct stages: extracting 2D frames from captured content, reconstructing 3D structures from multiple 2D images, training models on prepared data, and generating final 3D content using point-based representations like Gaussian splats. This segmentation reduces processing complexity by breaking down the complex transformation into manageable, modular steps that can be processed sequentially.
Solution Approach 2:
The patent performs preliminary actions by extracting and preparing 2D frames from captured content before 3D reconstruction. Training data preparation including frame extraction and 3D structure reconstruction is done in advance, creating a structured foundation that simplifies the subsequent 3D model generation process and reduces real-time processing complexity.
3Manufacturing precision
If multiple 2D frames from different angles are extracted and processed, then 3D reconstruction quality is improved, but data processing requirements increase
Solution Approach 1:
The patent extracts only the essential 2D frames from captured content that are necessary for 3D reconstruction, rather than processing all captured data. By selectively extracting frames from multiple angles and using these extracted frames as training data, the system achieves high 3D reconstruction accuracy while minimizing the volume of data that needs to be processed and stored.
Data Source
AI summary
Generating and sharing interactive three dimensional (3D) content/3D models captured from gaming sessions are described herein. The 3D content is able to be shared with mobile devices, televisions, gaming consoles, Virtual Reality (VR) devices or other devices. Since the content is rendered in 3D, a user is able to change the view direction, zoom in/out, and perform other functions. A framework enables video game media galleries to capture, view, edit, and share interactive, static or dynamic 3D media while keeping the structure of the original gaming assets inaccessible to the end-user.