Auxiliary Observation Apparatus Semantic Difference Detection
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Solution Overview
Problem
Existing auxiliary observation methods require pre-selected comparison objects and rely on visual characteristics, which can lead to missing important information or highlighting redundant information, reducing efficiency in observing multimedia data.
Innovation Solution
An auxiliary observation method and apparatus that determine comparison objects based on features of the observation target, such as context, metadata, and semantic meaning, to highlight significant differences, thereby improving the detection of important information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If difference comparison is implemented based on visual characteristics (color, shape, brightness, size), then visual differences between images are highlighted, but important information with minor visual differences (e.g., numerical values 0.9999999 and 1.0) may be missed
Solution Approach 1:
The patent changes the comparison parameters from visual characteristics (color, shape, brightness, size) to semantic characteristics (context, metadata, meaning). This allows important information with minor visual differences to be detected by comparing semantic equivalence rather than visual appearance, thereby improving detection precision without losing important information
Solution Approach 2:
The patent introduces semantic analysis as an intermediary layer between visual comparison and difference detection. By analyzing context, metadata, and meaning of image regions, the system mediates the comparison process to identify semantically important differences that visual characteristics alone cannot detect
2Productivity
If conventional visual characteristic comparison is used, then some differences are highlighted, but redundant unimportant information is also highlighted, reducing observation efficiency
Solution Approach 1:
The patent changes the comparison basis from visual parameters to semantic parameters, enabling the system to distinguish between visually different but semantically equivalent regions (redundant information) and visually similar but semantically different regions (important information), thereby improving observation efficiency by filtering out redundant highlights
Solution Approach 2:
The patent applies different comparison strategies to different regions of images based on their semantic importance. By analyzing context and metadata locally, the system determines which regions require detailed comparison and which can be quickly dismissed as redundant, optimizing the overall observation process
3Adaptability or versatility
If two observation objects are compared using existing methods, then some differences are detected, but the method requires comparison objects to be given in advance and cannot adapt to dynamic observation needs
Solution Approach 1:
The patent enables the system to automatically select and determine appropriate comparison objects based on semantic analysis of the target object's context and metadata, rather than requiring manual pre-selection. The system serves itself by intelligently identifying what should be compared based on semantic relevance, improving adaptability without proportionally increasing complexity
Solution Approach 2:
The patent performs preliminary semantic analysis of the target object (context, metadata, meaning extraction) before conducting the actual comparison. This preliminary action prepares the system to automatically determine appropriate comparison objects and criteria, making the overall process more adaptable while managing complexity through structured preprocessing
Data Source
AI summary
The present application discloses an auxiliary observation method and an auxiliary observation apparatus, and relates to the field of multimedia information processing technologies. The method comprises the following steps: determining at least one comparison object according to a feature of an observation target; and determining a part of or all differences between the observation target and the at least one comparison object. The method and the apparatus in embodiments of the present application can prevent a case in which important information is overlooked or redundant unimportant information is highlighted, and also improve efficiency of observing information, in particular important information.