Video Encoding Quality Adaptation via Viewing History
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Solution Overview
Problem
Existing video encoding systems waste storage medium capacity by encoding all video data with high image quality, regardless of user interest, leading to inefficient use of recording media.
Innovation Solution
An image-processing apparatus and method that determine a user's interest in scenes based on viewing history data, re-encoding video data with high quality only for interested scenes and lower quality for uninteresting scenes, dynamically adjusting the bit rate for transcoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If all video data is encoded with high image quality, then image quality is improved, but storage medium capacity is wasted
Solution Approach 1:
The patent applies local quality by differentiating encoding quality based on spatial and temporal characteristics of video content. Scenes containing performers of interest are encoded with high image quality, while other scenes use lower quality encoding. This resolves the contradiction by making image quality local rather than uniform across all video data.
Solution Approach 2:
The patent dynamically changes encoding parameters (bit rate, resolution, compression level) based on scene analysis and viewing history. When a scene contains a performer of interest, the system increases bit rate and quality parameters; otherwise, it reduces them. This parameter adaptation resolves the contradiction between maintaining high quality and conserving storage capacity.
2Quantity of substance
If video data is re-encoded at lower bit rate, then data amount is reduced, but image quality deteriorates
Solution Approach 1:
The patent applies local quality by differentiating encoding quality based on spatial and temporal characteristics of video content. Scenes containing performers of interest are encoded with high image quality, while other scenes use lower quality encoding. This resolves the contradiction by making image quality local rather than uniform across all video data.
Solution Approach 2:
The patent applies partial action by selectively applying high-quality encoding only to portions of video data that contain performers of interest, rather than encoding all video data at high quality. This partial application of high-quality encoding reduces overall data amount while maintaining acceptable image quality for important content.
3Measurement precision
If encoding quality is increased for scenes with performers, then user interest accuracy is improved, but storage capacity is reduced
Solution Approach 1:
The patent uses viewing history as feedback to identify performers of interest and adjust encoding quality accordingly. The system analyzes past viewing behavior to determine which performers users watch most frequently, then applies high-quality encoding preferentially to scenes containing these performers. This feedback mechanism improves user interest accuracy while optimizing storage capacity allocation.
Solution Approach 2:
The patent dynamically changes encoding parameters (bit rate, resolution, compression level) based on scene analysis and viewing history. When a scene contains a performer of interest, the system increases bit rate and quality parameters; otherwise, it reduces them. This parameter adaptation resolves the contradiction between maintaining high quality and conserving storage capacity.
Data Source
AI summary
An image-processing apparatus is configured to read encoded video data from a recording medium, decode the encoded video data, and re-encode the decoded video data. Further, the image-processing apparatus is configured to record information about a viewing-operation-history relating to the encoded video data and determine a target bit rate of the re-encoding based on the information about the viewing-operation-history. An image-processing method includes reading encoded video data from a recording medium, decoding the encoded video data, detecting information about a viewing-operation history relating to the encoded video data, re-encoding decoded video data obtained at the decoding step, and determining a target bit rate of the re-encoding performed at the encoding step based on the information about the viewing-operation-history.


