Automated Dance Segment Recognition via Audio-Video Threshold Analysis
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Solution Overview
Problem
Current methods for identifying dance segments in online class videos are inefficient and prone to errors, requiring manual processing which is time-consuming and labor-intensive, especially when dealing with large volumes of videos.
Innovation Solution
A dance segment recognition method that extracts audio and video segments, using neural networks to identify music segments and detect dance moves by analyzing image frames for specific thresholds, thereby automating the identification process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processing is used to identify dance segments in online class videos, then accuracy can be maintained through human judgment, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual mechanical review with an automated computer-based system that uses audio analysis to detect music segments and video analysis to detect dance moves, automatically identifying dance segments without human intervention while maintaining accuracy through algorithmic detection
Solution Approach 2:
The system enables self-service by allowing the computer to autonomously process videos, extract audio and video segments, analyze them independently, and automatically determine dance segments based on predefined criteria without requiring manual verification or intervention
2Reliability
If manual processing is used to identify dance segments in large volumes of videos, then quality control can be maintained, but productivity becomes extremely low
Solution Approach 1:
The patent divides the video processing task into independent audio segment extraction and video segment analysis components, allowing parallel processing of multiple video files simultaneously, which dramatically increases productivity while maintaining quality through consistent algorithmic application
Solution Approach 2:
The system uses objectively measurable parameters such as audio frequency patterns for music detection and skeletal motion parameters for dance move detection, replacing subjective human judgment with quantifiable metrics that ensure consistent quality across large volumes of processed videos
3Productivity
If automated methods are introduced to increase processing speed, then productivity improves, but accuracy and reliability may deteriorate due to algorithmic errors
Solution Approach 1:
The system incorporates feedback mechanisms where the computer automatically adjusts detection thresholds and parameters based on analysis results, refining its accuracy through iterative processing while maintaining high speed automated operation without sacrificing precision
Data Source
AI summary
A dance segment recognition method includes: extracting an audio segment from a video segment in response to the audio segment including a music segment with a time length greater than or equal to a pre-specified time length, using a video sub-segment that is included in the video segment and that corresponds to the music segment as a candidate dance segment and in response to a quantity of image frames showing a dance move in a plurality of image frames of the candidate dance segment being greater than a first pre-specified threshold, determining the candidate dance segment to be a dance segment. The dance segment recognition method can increase the speed of recognizing a dance segment in a video segment.