Relationship Extracting Apparatus for Event Context Analysis
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Solution Overview
Problem
Existing techniques for extracting key frames from events of interest do not provide information beyond what is included in the event itself, lacking relevance to broader contextual information.
Innovation Solution
A relationship extracting apparatus and method that acquires event information, determines a target duration based on event features, and extracts action-related relationships from object relationships information within that duration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If key frame extraction is performed only from event time, then processing speed is improved, but information completeness deteriorates
Solution Approach 1:
The patent applies preliminary action by extending the extraction window backward in time from the event occurrence moment. Instead of extracting only at the event time point, the system pre-determines a duration that includes a period before the event, allowing contextual information to be captured in advance while maintaining efficient processing through automated duration calculation based on event type.
Solution Approach 2:
The patent introduces a temporal dimension extension by transforming the extraction approach from a single time point (event time) to a time interval (duration including pre-event period). This dimensional change from point to interval in the time domain enables comprehensive information capture while preserving processing efficiency through structured duration management.
2Loss of information
If extraction duration is extended to include pre-event period, then information relevance is improved, but processing time increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the extraction duration parameter based on event type characteristics. Different event types are assigned different duration values, allowing the system to optimize the balance between information relevance and processing time for each specific event scenario, rather than using a fixed extraction window for all events.
Solution Approach 2:
The patent implements dynamics by making the extraction duration flexible and adaptive rather than static. The duration is determined dynamically based on the specific event type and its characteristics, enabling the system to automatically adjust the pre-event period length to achieve optimal information relevance while controlling processing time variations across different event scenarios.
Data Source
AI summary
A relationship extracting apparatus acquires event information that indicates features of an event of interest, determine target duration based on one or more features of the event of interest, and extract one or more action-related relationships that exist during the target duration from object relationships information. The object relationship information indicates two or more action-related relationships between objects in association with time at which or during which the action-related relationship exists.