Surveillance Image Analysis via Event Correlation
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Solution Overview
Problem
Conventional surveillance systems require manual searching of thousands of images, leading to inefficient and inaccurate identification of relevant information for security and crime prevention, due to limitations in existing technologies.
Innovation Solution
A surveillance system and method that utilizes image capturing devices and processors to automatically analyze the correlation between field information and event information, including time and detailed data, to determine the occurrence frequency of specific events, thereby identifying the most associated surveillance images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual searching of surveillance images is used, then system complexity is reduced, but productivity and measurement precision deteriorate due to inefficient and inaccurate identification of relevant information
Solution Approach 1:
The patent replaces manual mechanical searching with automated computer-based image analysis. The system uses computing devices to automatically extract features from surveillance images, perform content analysis, and identify relevant images based on predefined criteria, eliminating the need for manual review while significantly improving productivity and accuracy.
Solution Approach 2:
The surveillance system performs self-service by automatically analyzing its own image data without external human intervention. The computing device autonomously processes surveillance images, extracts meaningful features, correlates them with event information, and generates identification results, making the system self-sufficient in identifying relevant images.
2Measurement precision
If manual surveying of surveillance images is used, then device complexity is minimized, but measurement precision and reliability deteriorate due to lower data accuracy
Solution Approach 1:
The patent replaces inaccurate manual surveying with precise automated image analysis. The system uses computer algorithms to objectively extract features, calculate correlations with event information, and determine relevance based on quantitative metrics, eliminating human error and subjectivity while achieving consistent high-precision results.
Solution Approach 2:
The system implements feedback mechanisms by continuously comparing extracted image features with event information and adjusting the identification process accordingly. The computing device analyzes the correlation between image content and event data, refines its selection criteria based on predefined rules, and generates improved identification results through iterative processing.
Data Source
AI summary
A surveillance system including at least one image capture device and a processor, and a surveillance method are provided. The image capture device is coupled to the processor and captures surveillance images. The processor analyzes the correlation between multiple on site data corresponding to the surveillance images and event information. Each on site data includes time information and detail information. Therefore, the processor determines that the event information is more relevant to the surveillance image corresponding to the detail information having a higher occurrence frequency in the duration of the event information.