Intrusion Detection Region Segmentation for Faster Position-Based Alerts
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image surveillance techniques set a single intrusion duration time for auxiliary warning regions, which does not account for varying intrusion positions, leading to potential delays in alerting for objects that intrude more quickly.
Innovation Solution
An intrusion detection device that detects intrusion positions and associates them with specific time periods, outputting an alert when an object stays in a region for a predetermined time period based on the detected position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single intrusion duration time is set for the auxiliary warning region, then the system is simple to operate, but detection accuracy deteriorates due to delayed alerts for objects intruding more quickly
Solution Approach 1:
The auxiliary warning region is divided into multiple sub-regions, each with its own intrusion duration time setting. This segmentation allows different time thresholds to be applied to different spatial zones, improving detection accuracy for objects with varying intrusion speeds while maintaining manageable system complexity through modular configuration.
Solution Approach 2:
Different intrusion duration times are assigned to different positions within the auxiliary warning region based on local characteristics. This local quality approach enables the system to adapt time thresholds to specific spatial locations, allowing faster response for critical zones while maintaining simplicity through position-based differentiation.
2Loss of time
If a single intrusion duration time is used for all positions, then the system is easy to configure, but response time worsens for objects that intrude more quickly
Solution Approach 1:
The auxiliary warning region is segmented into multiple sub-regions, each with optimized intrusion duration times. This reduces time loss for quickly intruding objects by providing shorter thresholds in critical zones, while configuration ease is maintained through automated or template-based segmentation methods.
Solution Approach 2:
The intrusion duration time becomes a dynamic parameter that varies by position within the auxiliary warning region rather than a static global value. This dynamic approach optimizes response time for different intrusion scenarios while configuration tools provide dynamic template selection to ease the setup process.
3Adaptability or versatility
If the auxiliary warning region is set in a wide range to cover all possible intrusion paths, then detection coverage is improved, but the region becomes complex in shape conforming to image-capturing range
Solution Approach 1:
The complex auxiliary warning region is segmented into multiple simpler sub-regions that collectively provide wide coverage. Each sub-region has a simpler geometric shape that is easier to define and configure, while the combination of sub-regions achieves comprehensive detection coverage across all intrusion paths.
Solution Approach 2:
The system transitions from defining a single complex two-dimensional region to defining multiple simpler regions with hierarchical relationships. This dimensional change in the configuration approach allows wide coverage to be achieved through layered or zoned definitions rather than a single complex polygon.
Data Source
AI summary
A setting assistance device includes an acquisition unit, a calculation unit and a determination unit. The acquisition unit acquires coordinates designated by a user for an image capturing a three-dimensional space. The calculation unit calculates coordinates of a position located at a predetermined distance from a position of a part of the three-dimensional space relating to the acquired coordinates. The determination unit determines a region set for the acquired coordinates based on the calculated coordinates.