Automated Video Construction Engine for Real-Time Personalization
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Solution Overview
Problem
Current methods for constructing personalized video clips are costly and impractical for real-time, on-demand applications due to the need for manual intervention and high-end hardware, limiting their effectiveness in fields like medicine and advertising.
Innovation Solution
A system and method for automatically constructing personalized video clips based on viewer parameters, using a Video Script Engine to create instructional videos that can be produced in near real-time or real-time, suitable for medical instructions or other purposes, and convertible to audio format for aural consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual intervention is used to construct personalized video clips, then personalization quality is improved, but production cost and time increase significantly
Solution Approach 1:
The video construction process is divided into modular segments including template selection, parameter extraction from viewer data, automated script generation, and scene assembly. This segmentation enables parallel processing and automation while maintaining personalization quality through configurable template parameters.
Solution Approach 2:
An automated video construction system acts as an intermediary between raw viewer parameters and final personalized video output. The system uses intermediate representations including structured data models, script templates, and scene graphs to bridge the gap between input data and video generation, enabling real-time processing.
2Manufacturing precision
If high-end hardware is used for real-time video construction, then video quality is improved, but hardware cost increases
Solution Approach 1:
The system uses software-based video synthesis and rendering techniques to create high-quality video output without requiring expensive specialized hardware. Virtual camera models, procedural texture generation, and software ray tracing replace physical cinematography equipment, achieving cinematic quality through computational methods.
Solution Approach 2:
Traditional mechanical video production systems involving physical cameras, lighting equipment, and editing hardware are replaced with software-based pipelines. The system uses GPU-accelerated rendering, algorithmic scene generation, and digital compositing to substitute mechanical production processes, reducing hardware requirements while maintaining quality.
3Adaptability or versatility
If personalized video clips are constructed in real-time, then viewer engagement is improved, but processing speed requirements increase
Solution Approach 1:
Video templates, scene configurations, and script structures are prepared in advance during an offline setup phase. Parameter extraction rules, transition sequences, and asset libraries are pre-processed and stored in optimized formats. This preliminary preparation enables the runtime system to perform only parameter substitution and basic composition operations, achieving real-time generation from viewer data.
Data Source
AI summary
System and method for flexible video construction, particularly of a personalized video clip which provides instructions to a viewer with regard to health and wellness. An ordered list of video input files is chained together, to create a single output video file using a chosen container. Timestamp values are tracked, to ensure synchronization of multiple joined clips, optionally using adjustments of the audio channel or the video channel. A video construction server utilizes information from multiple sources, to construct the video clip.