Interactive Image Generation With Partial 3D Scene Synthesis
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Solution Overview
Problem
Existing techniques for generating three-dimensional models or specifications for interactive images are resource-intensive and prohibitive for many applications, making efficient interactive image generation difficult.
Innovation Solution
A content generation platform that combines actually captured content with computer-generated content using neural networks, allowing for the creation of interactive imagery with partial three-dimensional capabilities, enabling features like modifying composition, lighting, and background, without the need for a complete three-dimensional model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If complete three-dimensional models or specifications are generated using existing techniques, then interactive image features can be provided, but the process becomes resource intensive and prohibitive
Solution Approach 1:
The patent creates a synthetic three-dimensional model by copying and integrating features from multiple two-dimensional images rather than generating a complete model from scratch. The system extracts depth maps, segmentation masks, and other features from 2D images and synthesizes a 3D representation that provides interactive capabilities without requiring resource-intensive complete model generation
Solution Approach 2:
The system performs partial three-dimensional model generation by creating only the necessary components for interactive features rather than complete models. It generates depth maps, segmentation masks, and synthetic 3D representations only where needed to enable image manipulation, lighting changes, and composition modifications, avoiding the resource overhead of full model creation
2Adaptability or versatility
If complete three-dimensional models are generated, then interactive features are enabled, but the process time increases significantly
Solution Approach 1:
The system performs preliminary processing by pre-extracting features such as depth maps, segmentation masks, and surface normals from the input two-dimensional images before the interactive operations are needed. This preliminary action creates a prepared synthetic 3D model structure that can be quickly manipulated for various interactive features without requiring time-consuming model generation during actual use
Solution Approach 2:
The patent synthesizes a three-dimensional model by copying and integrating extracted features from multiple 2D images, enabling rapid model creation. This copying approach allows the system to generate interactive 3D representations from existing image data much faster than traditional complete model generation methods
3Manufacturing precision
If photorealistic interactive imagery is generated with full three-dimensional capabilities, then image quality is high, but computational resources and time are excessively consumed
Solution Approach 1:
The system changes the approach from generating complete high-precision 3D models to creating synthetic 3D representations with selectively applied precision. It uses parameter-based control to generate photorealistic imagery only where needed, adjusting the level of detail and computational precision based on the specific interactive feature being implemented, thereby maintaining image quality while improving generation efficiency
Solution Approach 2:
The patent achieves photorealistic image quality by copying and integrating high-fidelity features such as depth maps, segmentation masks, surface normals, and material properties from multiple input images. This copying approach preserves the visual quality of the original images while creating a synthetic 3D structure that enables interactive manipulation without requiring complete high-precision model generation
Data Source
AI summary
A content generation platform is generally described herein. More specifically, interactive image generation and techniques and features thereof are disclosed herein. One or more sets of images of a scene are captured in an imaging studio. The captured one or more sets of images of the scene are processed using one or more machine learning based networks to generate an interactive image of the scene comprising a plurality of interactive features. One or more of the plurality of interactive features of the generated interactive image may be modified or edited according to user preferences.