Audio-Based Video Annotation Using Feature Extraction
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Solution Overview
Problem
Existing video analysis techniques are time-consuming, expensive, and often result in incomplete or inaccurate annotation of video content, as they either rely on ad hoc methods or subsample video information, leading to crude analysis.
Innovation Solution
A computer system that extracts audio features from video content items to determine annotation items without analyzing the video information, using techniques such as unsupervised learning and supervised learning models to characterize audio features and improve annotation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video information is analyzed to determine annotation items, then annotation accuracy is improved, but analysis time and computational cost increase
Solution Approach 1:
The patent extracts audio information from video content as a separate, independent feature source. Instead of analyzing the entire video, the system extracts and analyzes only the audio track to determine annotation items, thereby reducing analysis time while maintaining annotation accuracy through the use of discriminative audio features
Solution Approach 2:
The patent segments the video analysis problem into distinct feature types (audio features, video features, text features) and processes them separately. By focusing on audio features alone for certain annotation tasks, the system avoids the computational burden of analyzing all video information while still achieving accurate annotations
2Loss of information
If all video information is analyzed to determine annotation items, then annotation completeness is improved, but computational intensity increases
Solution Approach 1:
The patent applies partial action by analyzing only the audio portion of video content rather than all video information. The system extracts comprehensive audio features including spectral, temporal, and chroma features to achieve sufficient annotation completeness without the excessive computational cost of full video analysis
Solution Approach 2:
The patent changes the analysis parameter from visual video data to audio data. By transforming the input modality from video frames to audio signals and analyzing different feature parameters (spectral content, temporal characteristics, chroma features), the system achieves annotation with reduced computational intensity
3Ease of manufacture
If existing ad hoc methods are used to determine annotation items, then implementation simplicity is improved, but annotation accuracy deteriorates
Solution Approach 1:
The patent replaces manual ad hoc annotation methods with an automated audio-based annotation system. The system automatically extracts audio features, processes them through learned models, and generates annotation items without human intervention, thereby maintaining implementation simplicity while dramatically improving annotation accuracy through systematic audio analysis
Data Source
AI summary
A technique for determining annotation items associated with video information is described. During this annotation technique, a content item that includes audio information and the video information is received. For example, a file may be downloaded from a uniform resource locator. Then, the audio information is extracted from the content item, and the audio information is analyzed to determine features or descriptors that characterize the audio information. Note that the features may be determined solely by analyzing the audio information or may be determined by subsequent further analysis of at least some of the video information based on the analysis of the audio information (i.e., sequential or cascaded analysis). Next, annotation items or tags associated with the video information are determined based on the features.