Security Device Zones with Irregular Boundaries
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Solution Overview
Problem
Current security systems face challenges in user understanding and efficiency when creating and maintaining zones within a field of view, due to inefficient user interfaces and the requirement for rectangular bounding boxes, leading to inaccuracies in object recognition and increased resource consumption.
Innovation Solution
The implementation of zone graphical user interfaces (GUIs) that allow users to define zones with pre-sized boxes or any shape, along with automatic image segmentation techniques, enabling precise and efficient zone creation and maintenance, and the use of semantic regions for accurate zone identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If rectangular bounding boxes are used to define zones, then the user interface is simple, but the accuracy of object recognition deteriorates due to inability to match irregular object shapes
Solution Approach 1:
The patent segments the field of view into multiple zones with irregular boundaries that can be independently defined. Each zone can be shaped to match specific areas of interest, allowing precise object recognition within each segmented region while maintaining overall system simplicity through modular zone management.
Solution Approach 2:
The patent implements asymmetric zone shapes that conform to the actual geometry of monitored areas and objects. Instead of forcing all zones into symmetric rectangular bounding boxes, the system allows zones to have irregular polygons and custom boundaries that match the asymmetric nature of real-world scenes, improving recognition accuracy.
2Measurement precision
If complex zone shapes are allowed, then object recognition accuracy improves, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The patent performs preliminary zone definition and boundary establishment during system setup or before monitoring begins. Zones are pre-configured with their irregular shapes and boundaries, allowing the monitoring system to simply check whether detected objects fall within predefined zones without performing complex geometric calculations in real-time, thus reducing processing complexity during operation.
Solution Approach 2:
The patent uses simplified representations or copies of zone boundaries (such as pixel masks or pre-computed zone maps) instead of storing and processing complex mathematical descriptions of irregular shapes. This allows the system to maintain high recognition accuracy while reducing computational complexity by using lightweight zone representations for comparison operations.
3Manufacturing precision
If manual zone definition is required, then zone accuracy improves, but the time consumption increases for users to create and maintain zones
Solution Approach 1:
The patent implements automatic zone suggestion features where the system analyzes the field of view and automatically proposes zone configurations based on detected objects, scene understanding, or historical data. Users can accept these automated suggestions with minimal modification, combining AI-driven automation with user confirmation to achieve high zone accuracy while significantly reducing the time users spend on manual zone creation and maintenance.
Data Source
AI summary
A method is provided. The method includes receiving, from a monitor interface implemented by a first computing device, input specifying a zone within a field of view of an image capture device; storing, in response to reception of the input, a record defining the zone; receiving, from the image capture device, an image acquired within the field of view by the image capture device; and rendering, via a customer interface implemented by a second computing device distinct from the first computing device, the image with a representation of the zone overlaid upon the image.