Region of Interest Video Coding with Adaptive Bit Rate Control
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Solution Overview
Problem
Existing variable bit rate encoding techniques for video frames are computationally intensive and difficult to adjust, necessitating improved methods for determining regions of interest and encoding quality.
Innovation Solution
A video processing unit comprising a region of interest detector, video encoder, and rate controller that differentially encodes regions of interest and non-regions of interest using specific bit rates, with the rate controller adjusting parameters based on requested quality and estimated complexity to generate a compressed bit stream.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If variable bit rate encoding is used to encode regions of interest with higher bit rate, then image quality of regions of interest is improved, but computational complexity increases
Solution Approach 1:
The video frame is segmented into regions of interest and non-regions of interest using bounding boxes. The ROI detector identifies multiple ROIs independently, allowing selective encoding strategies to be applied to different segments. This segmentation enables the system to focus computational resources only on important regions rather than processing the entire frame uniformly.
Solution Approach 2:
Different encoding qualities are applied to different regions of the video frame. Regions of interest are encoded with higher bit rates and better quality parameters, while non-ROI regions use lower bit rates. This local quality approach optimizes overall perceived quality by concentrating resources where they provide the most value.
2Manufacturing precision
If variable bit rate encoding is used for regions of interest and non-regions of interest, then image quality is improved, but ease of operation deteriorates
Solution Approach 1:
The rate controller dynamically adjusts encoding parameters based on feedback from the video encoder and changing conditions. The system can adaptively modify bit rate allocations, quantization parameters, and ROI definitions in real-time based on buffer status, available bandwidth, and detected scene changes, making the system easier to operate across varying conditions.
Solution Approach 2:
The system allows flexible adjustment of multiple encoding parameters including bit rate, quantization parameters, and ROI definitions. These parameters can be modified independently to achieve different quality targets or adapt to changing network conditions, improving ease of operation and configurability.
3Manufacturing precision
If higher bit rate is used to encode regions of interest, then image quality of regions of interest is improved, but bandwidth utilization increases
Solution Approach 1:
Higher bit rates and better quality are applied only to regions of interest rather than the entire video frame. Non-ROI regions are encoded at lower bit rates, significantly reducing the total bandwidth required while maintaining high perceived quality in important areas.
Solution Approach 2:
The system applies encoding resources partially and selectively - concentrating bandwidth on ROI regions that require high quality while using minimal resources for non-ROI regions. This partial action approach achieves high overall quality perception without the excessive bandwidth consumption of uniform high-quality encoding.
4Manufacturing precision
If region of interest detection and variable bit rate encoding are implemented, then image quality is improved, but device complexity increases
Solution Approach 1:
The video processing system is segmented into distinct functional modules: ROI detector, rate controller, and video encoder. Each module has a specific function and can be independently configured or optimized. This modular segmentation reduces system complexity by making each component simpler and more manageable.
Solution Approach 2:
The rate controller serves multiple functions: it manages bit rate allocation, controls encoding parameters, monitors buffer status, and adapts to changing conditions. This multi-functionality reduces the need for separate dedicated components, simplifying the overall system architecture while maintaining high image quality.
Data Source
AI summary
Video coding techniques including differential bit rate or quality coding of one or more regions of interest and one or more non-regions of interest based on information including one or more of coordinates of the one or more regions of interest, a target complexity, residual encoder bit data, a requested quality, a difference between the current video data frame and a reconstructed video data frame, a target quality, a requested bit rate, frame target bit allocation and an as encoded bit rate.