Video Encoding Apparatus with Dynamic Region of Interest Adaptation
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Solution Overview
Problem
Existing video encoding systems lack the ability to dynamically adjust the region of interest based on user-specific scenarios, leading to inefficient compression of high-resolution images, as the definition of region of interest and non-region of interest is often standardized across all users.
Innovation Solution
A video encoding apparatus and system that stores interest region information for various scenarios, allowing users to recognize and update the region of interest based on user input, dividing frames into blocks corresponding to region of interest and non-region of interest, and applying different quantization parameter values for efficient encoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the same criteria are used to define region of interest and non-region of interest for all users, then the device complexity is reduced and ease of operation is improved, but the adaptability to user-specific scenarios deteriorates
Solution Approach 1:
The system dynamically adjusts the region of interest definition based on detected scenarios. Different encoding parameters are applied automatically when different scenarios are detected, making the system adaptable without requiring complex manual configuration by users.
Solution Approach 2:
The system automatically detects scenarios and manages region of interest settings without user intervention. The self-service mechanism handles scenario-based adaptation internally, reducing the burden on users while maintaining high adaptability.
2Manufacturing precision
If different quantization parameter values are applied to region of interest and non-region of interest blocks, then the image quality in regions of interest is improved, but the device complexity increases
Solution Approach 1:
Different quantization parameter values are applied to different regions (region of interest vs. non-region of interest) within the same video frame. This local quality differentiation ensures high image quality in important regions while maintaining acceptable quality elsewhere, optimizing overall encoding efficiency.
Solution Approach 2:
The video frame is segmented into region of interest blocks and non-region of interest blocks based on scenario detection. This segmentation enables differential encoding where each segment receives appropriate encoding parameters, improving overall image quality without uniformly increasing complexity across the entire frame.
3Adaptability or versatility
If scenario analysis is performed to extract interest region information, then the adaptability to different video scenarios is improved, but the processing time and computational resources increase
Solution Approach 1:
Scenario analysis and region of interest identification are performed as preliminary steps before the main encoding process. By detecting scenarios upfront and preparing region masks in advance, the system enables efficient encoding without repeated analysis during the encoding process, reducing overall processing time.
Data Source
AI summary
A video encoding apparatus may include a memory storing interest region information for each of a plurality of scenarios and a neural processing unit (NPU) extracting interest region information corresponding to a scenario of an input video from the memory or updating the interest region information stored in the memory based on an user input.