Pose Estimation for Automatic Video Music Synchronization
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Solution Overview
Problem
Manually synchronizing movement in videos to music and effects is difficult and time-consuming, making it a labor-intensive process.
Innovation Solution
A system that uses pose estimation to determine the movement of individuals in videos, allowing for automatic selection of music and application of visual effects that synchronize with the movement, thereby generating an edited video that matches the timing and rhythm of the music.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual synchronization of video movement to music and effects is performed, then precision of synchronization can be achieved, but time consumption and labor intensity increase significantly
Solution Approach 1:
The system enables automatic video editing by having the video content itself provide the synchronization signals through pose estimation. The movement and pose changes in the video automatically drive the editing decisions, eliminating the need for manual frame-by-frame analysis while maintaining synchronization precision.
Solution Approach 2:
The patent replaces manual mechanical editing processes with automated computer vision-based pose estimation and algorithmic synchronization. The system uses automated detection of pose landmarks and movement patterns to substitute for manual timing and synchronization operations.
2Productivity
If automated pose estimation is used to synchronize video to music, then editing productivity increases, but system complexity increases
Solution Approach 1:
The system segments the video analysis into distinct pose estimation components that track specific anatomical landmarks. This segmentation allows the complex task of movement analysis to be broken down into manageable detection of key points, distances, and pose changes that can be processed automatically.
Solution Approach 2:
The pose estimation system serves multiple functions simultaneously: it detects movement for synchronization, identifies highlight moments for effects application, and provides timing information for music alignment. This multi-functionality reduces overall system complexity by using a single automated framework for multiple editing tasks.
3Measurement precision
If detailed pose analysis is performed to detect highlight movements, then accuracy of effect synchronization improves, but computational requirements increase
Solution Approach 1:
The system applies local quality analysis by focusing pose estimation on specific anatomical landmarks and body parts that are most relevant for detecting highlight movements. Rather than analyzing every pixel or movement, the system concentrates computational resources on key pose features that provide the most information for synchronization and effect triggering.
Data Source
AI summary
Pose of a person depicted within a video may be determined. The pose of the person depicted within the video may be used to edit the video. Visual effects may be applied to the video based on the pose of the person depicted within the video. Timing of the video may be remapped to timing of music providing accompaniment for the video edit.