Multi-Camera Surveillance Error Correction via Analysis Unit
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Solution Overview
Problem
The reliability of intelligent video surveillance systems is compromised due to random errors caused by differences in hardware and software performance among internet protocol cameras (IPCs) and varying environmental conditions, leading to inconsistent analysis results.
Innovation Solution
A multi-camera collaboration-based image processing method where multiple IPCs obtain and process images independently, then send their results to an analysis unit to determine a unified execution result, reducing random errors and improving system reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple IPCs independently complete intelligent analysis on surveillance objects, then the system can process more surveillance areas, but random errors increase due to hardware and software differences among IPCs
Solution Approach 1:
The system divides the surveillance area into multiple zones, each monitored by a dedicated IPC. Each IPC independently analyzes objects within its segmented area, maintaining high processing capacity while enabling centralized error correction through the analysis unit that compares results across segments.
Solution Approach 2:
The analysis unit merges results from multiple IPCs by comparing execution results and identifying consistent surveillance objects. Objects detected by multiple IPCs with consistent characteristics are confirmed as valid, while random errors are filtered out through this merging process.
2Device complexity
If a single IPC performs intelligent analysis, then the system structure is simple, but the reliability and accuracy of surveillance object recognition is insufficient
Solution Approach 1:
The analysis unit serves as an intermediary between multiple IPCs and the central control system. It receives execution results from various IPCs, performs comparative analysis to eliminate random errors, and outputs reliable surveillance object information, thereby improving recognition accuracy without significantly increasing overall system complexity.
3Adaptability or versatility
If IPCs with different hardware and software performance are used, then system cost is reduced and adaptability is improved, but random errors in analysis results increase
Solution Approach 1:
The system allows different IPCs to operate with varying hardware and software configurations (parameter diversity) while the analysis unit normalizes their output by comparing execution results. This enables parameter changes across devices without compromising overall measurement precision, as the analysis unit compensates for individual device variations.
Data Source
AI summary
A video surveillance system includes at least two camera and an analysis device. The at least two cameras include a first image camera and a second image camera. The method includes: separately obtaining, by the first image camera and the second image camera, a photographed first image and a photographed second image; obtaining indication information of a target task; separately obtaining first execution result information and second execution result information of the target task based on the indication information of the target task; sending, the first execution result information and the second execution result information to the analysis device; and determining, by the analysis device, third execution result information of the target task based on the first execution result information and the second execution result information.