AV File Synchronization Using Vector Cubes and Optimal Subframes
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Solution Overview
Problem
The manual process of video post-production is time-consuming and requires trained professionals, preventing non-experts from creating professional-quality videos from multiple recorded segments.
Innovation Solution
A system that autonomously generates an optimized audio-visual file by creating a vector cube from an original AV file, applying filters to determine optimal subframes, and synchronizing multiple AV files to compile a seamless video.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual video post-production processes are used, then video quality can be maintained, but the process becomes prohibitively time-consuming and requires trained professionals
Solution Approach 1:
The system performs self-service by automatically analyzing video segments, determining optimal perspectives, and compiling the final video without human intervention. The computer executes algorithms to identify key moments, select camera angles, and synchronize audio-visual content, enabling the system to produce professional-quality videos autonomously
Solution Approach 2:
The patent replaces manual mechanical editing processes with automated computational systems. Instead of trained professionals manually cutting and assembling video segments, the system uses computer vision algorithms, machine learning models, and automated synchronization techniques to perform the same functions digitally and automatically
2Manufacturing precision
If multiple video cameras are used to record different perspectives, then video quality and professionalism improve, but the post-production complexity and time requirements increase
Solution Approach 1:
The system segments the video content into discrete analyzable units and processes each independently. It divides the task of analyzing multiple camera perspectives into separate evaluation steps for each video segment, determining optimal perspectives for each segment before compiling them into the final video
Solution Approach 2:
The system changes evaluation parameters dynamically based on content analysis. It adjusts criteria for selecting optimal perspectives depending on the specific video segment being analyzed, considering factors such as viewer engagement, action intensity, and narrative importance to determine the best camera angle for each moment
3Productivity
If automated processing is implemented, then productivity increases, but the system complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-processing video segments before final compilation. It预先 analyzes each segment to determine optimal perspectives, extracts key features, and prepares content for efficient assembly, reducing the complexity of the final compilation process
Solution Approach 2:
The patent introduces a new dimensional approach by creating a vector cube representation of video content. This multi-dimensional framework allows the system to evaluate and optimize video segments across multiple parameters simultaneously (temporal, spatial, and content dimensions), enabling efficient automated decision-making without excessive system complexity
Data Source
AI summary
One variation of a method for autonomously generating an optimized audio-visual (AV) file from an original AV file comprises: a) generating a vector cube comprising a plurality of vector matrices for an original AV file; b) for each vector matrix within the vector cube, determining an optimal subframe having a subframe size larger than or equal to a predetermined minimum subframe size; and c) generating an optimized AV file based on the optimal subframes determined for each of the vector matrices within the vector cube.