Surveillance Configuration Module for Object Classification
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Solution Overview
Problem
Existing surveillance systems face challenges in efficiently classifying and monitoring a large number of objects in surveillance scenes due to the complexity of manually configuring object property areas, which hinders effective automated image analysis.
Innovation Solution
A configuration module that allows users to select reference objects within a surveillance scene to define object property areas through user interaction, with options for setting tolerances and variations, simplifying the configuration process by using object properties as a basis for classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual configuration of object property areas is used, then classification accuracy can be achieved, but configuration complexity and time consumption increase significantly
Solution Approach 1:
The system automatically extracts object properties from surveillance images and generates object property areas without requiring manual configuration. The surveillance system itself performs the configuration task by analyzing actual object characteristics in the surveillance scene, making the system self-configuring and eliminating complex manual setup while maintaining accurate classification.
Solution Approach 2:
The system copies actual object properties from surveillance images to define object property areas. By extracting real object characteristics (size, shape, color, position) from captured images and using them as the basis for classification parameters, the system transfers actual operational data into configuration parameters, achieving both accuracy and automation.
2Measurement precision
If manual configuration of object property areas is used, then classification accuracy can be achieved, but time consumption for setup increases
Solution Approach 1:
The surveillance system automatically performs configuration by extracting object properties from surveillance images and generating object property areas autonomously. This self-service approach eliminates the time-consuming manual configuration process while maintaining accurate classification based on real object characteristics observed in the surveillance scene.
Solution Approach 2:
The system performs preliminary extraction of object properties from surveillance images to pre-configure object property areas before actual classification operations begin. By preparing classification parameters in advance through automatic analysis of actual objects, the system eliminates setup time while ensuring accurate classification parameters are ready for immediate use.
3Productivity
If automated object classification is implemented, then monitoring efficiency improves, but system complexity increases
Solution Approach 1:
The configuration module serves multiple functions: it extracts object properties from surveillance images, determines object property areas, and provides these parameters for classification. This multi-functional approach consolidates what could be separate complex modules into a single integrated component, improving monitoring efficiency while managing system complexity through functional consolidation.
Solution Approach 2:
The system automatically extracts object properties and generates classification parameters without requiring external configuration input. This self-service capability enables automated object classification to proceed with parameters derived directly from surveillance data, improving monitoring efficiency while avoiding the complexity of manual configuration interfaces and procedures.
Data Source
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AI summary
The invention relates to surveillance systems, for example, video surveillance systems, used to observe at least one region to be monitored, surveillance cameras being oriented towards the areas to be monitored. The video images recorded by the surveillance cameras are frequently transmitted to a central unit, for example a central surveillance station, and evaluated by surveillance personnel or in an automated manner. The invention also relates to a configuration module (7) for a surveillance system (1) which is designed to classify objects (9) having object characteristics in a surveillance scene (12) based on object characteristic regions as objects to be monitored. The configuration module (7) is used to define the object characteristic regions, and has a selection device (10, 13) for the interactive selection and/or confirmation of the selection of an object (9) as a reference object (14). The object characteristic regions are defined on the basis of and/or using the object characteristics of the reference object (14).