Video Encoding Regions of Interest Bandwidth Optimization
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Solution Overview
Problem
Video encoding systems face challenges in efficiently utilizing available bandwidth to maintain acceptable digital video quality, especially under stringent bandwidth restrictions, where not all regions of a video frame are equally important for perceptual quality and varying frame rates are required based on content characteristics.
Innovation Solution
The system segments digital video content into spatial and temporal regions of interest (ROIs) and adjusts encoding parameters accordingly, allocating higher bit rates to critical regions and varying frame rates based on content-specific characteristics to optimize visual quality at any given bit rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uniform bit rate allocation is used across all video regions, then encoding simplicity is maintained, but visual quality in important regions deteriorates
Solution Approach 1:
The patent applies local quality by dividing the video frame into multiple regions of interest (ROIs) and allocating different bit rates to different regions based on their importance. Important regions such as human faces and action areas receive higher bit rates for better visual quality, while less important background regions receive lower bit rates. This resolves the contradiction by making the encoding process adaptive to local content characteristics rather than applying uniform encoding across the entire frame.
Solution Approach 2:
The patent segments the video frame into multiple regions of interest using content analysis that identifies different types of regions (e.g., human faces, action areas, background). This segmentation enables differential bit rate allocation where each region can be encoded with appropriate quality levels based on its visual importance, thereby improving overall visual quality without requiring uniformly high bit rates across the entire frame.
2Manufacturing precision
If higher frame rates are used for all video content, then motion rendition quality is improved, but bandwidth consumption increases
Solution Approach 1:
The patent applies dynamics by making the frame rate adaptive based on the motion characteristics of different regions of interest. The system analyzes motion vectors and identifies regions with high motion activity, then dynamically adjusts the frame rate for those specific regions. Regions with high motion receive higher frame rates to maintain motion rendition quality, while static or low-motion regions are encoded at lower frame rates, thereby optimizing bandwidth consumption while preserving motion quality where needed.
3Manufacturing precision
If region-based differential encoding is implemented, then visual quality in important regions is improved, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by performing content analysis and region identification during an initial pass through the video data before the actual encoding process. The system pre-identifies regions of interest and determines their importance levels, then uses this pre-computed information to guide the differential encoding process. This preliminary segmentation and analysis separates the complex decision-making from the encoding process itself, making the overall system more manageable while still achieving region-based quality optimization.
Data Source
AI summary
Digital video content is processed for delivery over a communications channel by segmenting the digital video content into one or more regions of interest (ROI) in accordance with content signature of the video content and encoding the digital video content in accordance with the ROI segmentation and the communications channel.