Audio-Visual Frame Classification for Adaptive Content Rendering
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Solution Overview
Problem
Existing audio-visual content processing systems fail to effectively separate and process audio and visual frames independently, leading to suboptimal quality in the final output.
Innovation Solution
The system analyzes audio and visual frames separately, classifies objects within them, and applies distinct processing operations based on these classifications to enhance the intelligibility, immersiveness, and spaciousness of the audio-visual content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If audio and visual frames are processed together as integrated content, then processing simplicity is maintained, but processing quality and optimization are compromised
Solution Approach 1:
The system segments the integrated audio-visual content into separate audio frames and visual frames for independent processing. Each frame type undergoes specialized classification and processing operations tailored to its specific characteristics, thereby improving processing quality without requiring overly complex integrated processing
2Manufacturing precision
If uniform processing operations are applied to all audio frames, then processing simplicity is maintained, but processing effectiveness for different audio types is reduced
Solution Approach 1:
The system applies local quality by classifying audio frames into different types (e.g., speech, music, effects) and applying specific processing operations to each class. This allows each audio frame to receive customized processing tailored to its characteristics, improving effectiveness while managing complexity through systematic classification
3Manufacturing precision
If uniform processing operations are applied to all video frames, then processing simplicity is maintained, but processing effectiveness for different visual content is reduced
Solution Approach 1:
The system classifies video frames into different categories (e.g., scenes with people, landscapes, objects) and applies specific processing operations to each category. This enables optimized processing for different visual content types, improving effectiveness while maintaining manageable complexity through structured classification
Data Source
AI summary
A system and method for the generation of automatic audio-visual analytics for object rendering in capture. One example provides a method of processing audiovisual content. The method includes receiving content including a plurality of audio frames and a plurality of video frames, classifying each of the plurality of audio frames into a plurality of audio classifications, and classifying each of the plurality of video frames into a plurality of video classifications. The method includes processing the plurality of audio frames based on the respective audio classifications and processing the plurality of video frames based on the respective video classifications. Each audio classification is processed with a different audio processing operation, and each video classification is processed with a different video processing operation. The method includes generating an audio/video representation of the content by merging the processed plurality of audio frames and the processed plurality of video frames.