AI 3D Immersion Environment Generation for 2D Video Catalogs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for creating three-dimensional environments for two-dimensional video content are time-consuming and costly, requiring manual production by artists on a title-by-title basis, making them inefficient and impractical for large catalogs of video content.
Innovation Solution
An AI-based system using machine learning models automates the generation of three-dimensional background environments for two-dimensional video content, utilizing models like YOLOv8, SD-XL Inpainting, ZoeD-M12NK, and TripoSR to generate photo-realistic and immersive environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual production by artists is used to create 3-D environments for 2-D video content, then the quality and thematic appropriateness of the environments can be ensured, but the process becomes time-consuming and costly
Solution Approach 1:
The patent replaces the manual mechanical process of artists creating 3-D geometry models and texture maps with an automated AI-based system. The system uses machine learning models to automatically generate 3-D environments from 2-D video frames, eliminating the need for manual artistic production while maintaining quality through algorithmic optimization.
Solution Approach 2:
The system enables self-service by allowing the 3-D environment generation to occur automatically without human intervention. The AI-based generator autonomously processes video content, extracts relevant features, and produces themed 3-D backgrounds, making the process independent of manual artistic input.
2Adaptability or versatility
If manual production by artists is used to create 3-D environments for 2-D video content, then the environments can be customized for each title, but the process becomes costly and impractical for large catalogs
Solution Approach 1:
The patent creates a universal system that can process any 2-D video content and automatically generate appropriate 3-D environments. The AI-based generator is designed to handle diverse content types and themes, making it adaptable to large catalogs without requiring separate manual production processes for each title.
Solution Approach 2:
The system achieves customization by dynamically changing parameters such as color schemes, geometric patterns, and texture characteristics based on the analysis of each video content's thematic elements. The AI model adjusts these parameters automatically to match the mood and style of different video titles, maintaining adaptability at scale.
3Productivity
If automated AI-based generation is used to create 3-D environments, then the process becomes efficient and cost-effective, but the thematic appropriateness and quality may be compromised
Solution Approach 1:
The system incorporates feedback mechanisms where the AI model analyzes the generated 3-D environments and adjusts parameters based on thematic consistency with the source video content. The system uses feature extraction and comparison to ensure the generated environments maintain appropriate quality and thematic alignment.
Solution Approach 2:
The patent applies preliminary action by pre-training the AI models on diverse video content and 3-D environment datasets before actual generation. This pre-processing ensures the system has learned appropriate patterns and relationships, enabling it to produce high-quality themed environments efficiently during actual operation.
Data Source
AI summary
A system includes a hardware processor and a memory storing an artificial intelligence based (AI-based) content immersion environment generator. The hardware processor executes the AI-based content immersion environment generator to receive media content including multiple video frames, identify one or more video frames for use in generating a content immersion environment for display of the media content, and analyze features of each of the one or more video frames to provide one or more respective depth maps. The hardware processor further executes the AI-based content immersion environment generator to generate, based on the one or more video frames and using a trained AI model and the one or more respective depth maps, a three-dimensional (3-D) content immersion environment corresponding respectively to each of the one or more identified video frames to provide one or more 3-D content immersion environments for the display of the media content.