Video Encoding Circuit ROI Detection via Complexity Metrics
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Solution Overview
Problem
Conventional region of interest (ROI) detection techniques in video encoding are computationally complex and inefficient, particularly when applied to high-motion scenes, as they often require processing entire images rather than focusing on areas of significance.
Innovation Solution
A method that calculates complexity values of blocks in a current picture to identify regions of interest, adjusting these values to determine areas of higher and lower bit rates for efficient encoding, thereby reducing computational complexity and improving encoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional ROI detection techniques (face detection, edge detection) are used, then detection accuracy is improved, but computational complexity increases significantly
Solution Approach 1:
The patent uses the video encoder's own complexity metrics (from motion estimation and transformation processes) to automatically identify ROI regions. The encoder inherently calculates complexity values during normal operation, and these values are directly utilized for ROI detection without requiring separate detection algorithms, thus achieving accurate ROI identification with minimal additional computational overhead
Solution Approach 2:
The patent makes the complexity calculation process serve dual purposes: it performs both the standard video encoding function and the ROI detection function simultaneously. The same computational operations used for motion estimation and transformation also provide the complexity values needed for ROI identification, eliminating the need for separate dedicated ROI detection mechanisms
2Measurement precision
If conventional ROI detection techniques are applied, then detection capability is improved, but processing speed decreases
Solution Approach 1:
The patent maintains continuous video encoding processing while simultaneously performing ROI detection using the same computational operations. The complexity metrics are generated continuously during the encoding process itself, allowing ROI identification to occur without interrupting or slowing down the video processing pipeline, thus maintaining high processing speed while achieving accurate detection
3Device complexity
If fixed area ROI specification is used, then computational complexity is reduced, but detection accuracy deteriorates
Solution Approach 1:
The patent transitions from static fixed-area ROI specification to dynamic ROI identification based on actual video content characteristics. The complexity values are calculated for each block in real-time during encoding, automatically adapting to the specific motion and transformation characteristics of different video regions, thus achieving accurate ROI detection that dynamically responds to content variations without requiring complex preprocessing
Data Source
AI summary
An apparatus having a circuit. The circuit may be configured to (i) calculate a plurality of complexity values while compressing a current picture in a video signal. Each complexity value generally characterizes how a corresponding one of a plurality of blocks in the current picture was compressed. The circuit may also be configured to (ii) adjust the complexity values below a first threshold to a default value and (iii) generate a region of interest by grouping the blocks having non-default values of the complexity values above a second threshold.