Distributed Image Analysis for Event Detection
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Solution Overview
Problem
Current image analysis systems for event detection or recognition are inefficient due to reliance on human operators, high costs, and limited processing capabilities in camera-mounted processors, leading to increased false alerts and inadequate detection accuracy.
Innovation Solution
A method and apparatus for capturing digital image data, extracting feature information in real-time, and transmitting it to a remote device for further analysis, utilizing a distributed network of sensors, processors, and a server for intelligent event detection and recognition, including the combination of low-resolution images into high-resolution images for enhanced analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image analysis is performed using human operators, then detection accuracy can be maintained, but operational efficiency decreases and operational costs increase
Solution Approach 1:
The system enables self-service by implementing automated event detection through distributed sensors and processors that independently analyze images without requiring human operators. The sensors capture images, extract features, detect events, and transmit alerts autonomously, eliminating the need for manual monitoring while maintaining detection accuracy.
2Speed
If a processor is installed on the camera for local image processing, then response time improves, but processing capability is limited due to size, weight, cost, and power constraints
Solution Approach 1:
The system segments the image processing function across multiple distributed sensors and processors rather than relying on a single camera-mounted processor. Each sensor captures images and extracts features locally for rapid response, while the distributed network enables complex event detection that overcomes individual device limitations.
Solution Approach 2:
The system transitions from single-dimension local processing to multi-dimensional distributed processing by deploying sensors across different locations and processing levels. This spatial and functional distribution enables both fast local response and sophisticated global analysis simultaneously.
3Measurement precision
If all captured images are transmitted for analysis, then detection accuracy improves, but data transmission costs and network bandwidth requirements increase
Solution Approach 1:
The system extracts only essential feature information from captured images using distributed processors before transmission. By identifying and transmitting only relevant features rather than complete images, the system maintains detection accuracy while significantly reducing data transmission requirements and associated costs.
4Reliability
If dedicated coaxial cable or fiber optic lines are used for image signal transmission, then signal quality is maintained, but system cost and installation complexity increase
Solution Approach 1:
The system uses universal wireless communication protocols that can transmit both image data and control signals without requiring dedicated infrastructure. This multi-functional approach eliminates the need for separate coaxial or fiber optic lines, reducing system cost and installation complexity while maintaining reliable communication.
Data Source
AI summary
A method and apparatus for intelligent distributed analyses of images including capturing the images and analyzing the captured images, where feature information is extracted from the captured images. The extracted feature information is used in determining whether a predefined condition is met, and the extracted feature information is transmitted for further analysis when the predefined condition is met. The extracted feature information is stored and is used to generate statistical information related to the extracted feature information. Further, additional feature information is provided from other databases to implement further analysis including an event detection or recognition. Accordingly, distributed intelligent analyses of images is provided for analyzing captured images to efficiently and effectively implement event detection or recognition.