Semantic Region-Based Filtering for Video Frame Processing
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Solution Overview
Problem
Existing video encoding and decoding technologies lack the ability to adapt filtering operations based on semantic information, leading to suboptimal processing of different regions within a frame, which can affect the accuracy of neural networks and user viewing experience.
Innovation Solution
Implement region-based filtering using semantic information, such as position, size, and class information of objects within a frame, to apply different filtering strengths and operations, enhancing the accuracy of neural networks and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If uniform filtering is applied to all regions of a frame, then the processing is simple and fast, but the accuracy of neural networks and user viewing experience deteriorate due to suboptimal processing of different regions
Solution Approach 1:
The patent applies different filtering operations and strengths to different regions of the frame based on semantic information. Specifically, it identifies important regions (such as regions containing objects of interest) and applies stronger or different filtering compared to other regions, thereby improving neural network accuracy without uniformly increasing complexity across the entire frame.
Solution Approach 2:
The patent segments the frame into different regions based on semantic information before applying filtering. By dividing the frame into regions of interest and other regions, it enables targeted filtering strategies that improve accuracy where needed while maintaining simplicity in less critical areas, thus resolving the contradiction between precision and complexity.
2Measurement precision
If region-based filtering with semantic information is implemented, then the accuracy of neural networks and user viewing experience improve, but the processing complexity and computational resources increase
Solution Approach 1:
The patent performs preliminary segmentation of the frame into regions based on semantic information before the filtering operation. By pre-identifying important regions and determining the filtering strategy in advance, it avoids complex real-time decisions during filtering, thereby improving accuracy while minimizing the impact on processing efficiency.
3Reliability
If different filtering operations are applied to different regions, then the user viewing experience improves, but the device complexity and implementation difficulty increase
Solution Approach 1:
The patent implements region-based filtering by applying different filtering operations to different regions of the frame based on semantic information. This allows the system to enhance user viewing experience in important regions (such as regions containing objects of interest) while using simpler filtering in other regions, thereby improving reliability without uniformly increasing system complexity.
Data Source
AI summary
Various embodiments describe apparatus, method and computer program product. An example apparatus includes at least one processor; and at least one non-transitory memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to perform: receiving a frame to be filtered; receiving semantic information about the frame to be filtered; and filtering the frame based at least on the semantic information.