Multimedia Content Classification for Bit Rate Optimization
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Solution Overview
Problem
Current multimedia data processing methods do not effectively adjust bit rates based on content-specific characteristics, leading to discrepancies in video quality and inefficient bandwidth usage, as they typically encode all content types at constant quality or bit rates.
Innovation Solution
The method involves determining the spatial and temporal complexity of multimedia data, classifying it based on these complexities, and adjusting the bit rate accordingly to optimize encoding and ensure consistent perceived quality, using a content classification system that associates texture and motion values with bit rate allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If constant quality or bit rate encoding is used for all content types, then encoding simplicity is maintained, but video quality consistency and bandwidth efficiency deteriorate
Solution Approach 1:
The patent applies local quality by classifying video content into different complexity categories (low, medium, high) and applying different encoding quality levels to different regions of the video stream. Simple scenes receive lower quality encoding while complex scenes receive higher quality encoding, optimizing overall bandwidth efficiency while maintaining perceived quality consistency.
Solution Approach 2:
The patent implements dynamic encoding by continuously analyzing video content complexity and adjusting encoding parameters in real-time. The system dynamically switches between different encoding modes based on detected scene characteristics, motion levels, and temporal changes, rather than using a static constant quality approach.
2Ease of operation
If constant bit rate encoding is used for all content types, then bandwidth allocation is simplified, but encoding efficiency and video quality deteriorate
Solution Approach 1:
The patent changes encoding parameters dynamically based on content classification. It adjusts bit rate, quantization levels, and encoding complexity parameters according to the detected video scene type, motion magnitude, and temporal complexity, thereby optimizing encoding efficiency for each specific content segment.
Solution Approach 2:
The patent performs preliminary content analysis and classification before encoding to determine the appropriate bit rate and encoding parameters in advance. This pre-processing step identifies scene complexity and predicts required bandwidth allocation, allowing the encoder to be pre-configured for optimal performance on upcoming video segments.
3Manufacturing precision
If content-based classification is implemented, then video quality consistency and bandwidth efficiency improve, but processing complexity increases
Solution Approach 1:
The patent segments video content into distinct complexity categories (low, medium, high) based on spatial and temporal analysis. By dividing the continuous video stream into discrete complexity classes, the system simplifies the classification process while maintaining effective quality control across different scene types.
Solution Approach 2:
The patent implements a multi-functional classification system that simultaneously evaluates multiple video characteristics (spatial complexity, temporal complexity, motion magnitude) using a unified classification framework. This universal approach handles diverse content types through a single processing pipeline, reducing overall system complexity.
Data Source
AI summary
An apparatus and method for processing multimedia data, such as, for example, video data, audio data, or both video and audio data for encoding utilizing a determined content classification is claimed. Processing the multimedia data includes determining complexity of multimedia data, classifying the multimedia data based on the determined complexity, and, determining a bit rate for encoding the multimedia data based on its classification. The complexity can include a spatial complexity component and a temporal complexity component of the multimedia data. The multimedia data is classified using content classifications, which are based on a visual quality value for viewing multimedia data, using the spatial complexity, the temporal complexity, or both the spatial complexity and temporal complexity.