IP Video Surveillance System Using Segmented Search Regions
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Solution Overview
Problem
In large-scale video surveillance systems using IP-based networks, the computation required for extracting and storing image features from multiple cameras is high, leading to increased load and scalability issues, especially with inexpensive cameras having limited computation resources, while also needing to manage real-time transmission and historical data search.
Innovation Solution
A video surveillance system architecture that includes plural cameras, a monitoring apparatus, and a search apparatus, where the monitoring apparatus generates and transmits low-resolution image data and features to a search apparatus for storage, reducing computational load by using low-resolution data and event detection to minimize feature extraction, and allowing seamless real-time and historical information retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If image features are extracted and stored from images captured by multiple cameras in a large-scale monitoring system, then search capability for historical information is improved, but the computation load and system complexity increase significantly
Solution Approach 1:
The system divides the monitoring network into multiple search regions, with each search apparatus managing a specific region. This segmentation allows the search function to be distributed across multiple devices, reducing the complexity burden on any single apparatus while maintaining comprehensive search capability across the entire monitoring system.
Solution Approach 2:
The invention introduces a registration apparatus as an intermediary component that manages the registration of search results from multiple cameras. This mediator coordinates between cameras, search apparatuses, and the monitoring system, simplifying the overall system architecture by centralizing the coordination function and reducing direct complexity interactions between numerous camera and search apparatus pairs.
2Measurement precision
If image features are extracted from all captured images, then search accuracy is improved, but the computation time and processing load increase
Solution Approach 1:
The system performs feature extraction selectively rather than on all captured images. By registering search results and features only when necessary (e.g., when events are detected or when specific search criteria are met), the system maintains search accuracy for relevant data while significantly reducing unnecessary computation time and processing load on the monitoring apparatus.
Solution Approach 2:
The registration apparatus pre-registers search results and image features from multiple cameras before actual search operations are needed. This preliminary action allows the system to have search data ready in advance, reducing computation time during actual search operations while maintaining search accuracy through pre-processed feature data.
3Productivity
If multiple search apparatuses are deployed to handle large-scale monitoring, then search capacity is improved, but network load and system complexity increase
Solution Approach 1:
The monitoring system is divided into multiple search regions, each handled by a dedicated search apparatus. This segmentation increases search capacity by allowing parallel processing across multiple devices while reducing network load by localizing search operations to specific regions, minimizing the amount of data that needs to be transmitted across the entire network.
Solution Approach 2:
The registration apparatus serves as a mediator that coordinates search results from multiple search apparatuses. It manages the aggregation and distribution of search data, reducing redundant network transmissions and optimizing data flow between search apparatuses and the monitoring system, thereby increasing search capacity while controlling network load.
Data Source
AI summary
A technique capable of preventing an increase in the load of a system and a IP-based network that perform both a process of transmitting information in real time and a process of storing and searching history information and of improving the scalability of the system. A video surveillance system includes: plural cameras that capture images; a monitoring apparatus that displays the images captured by the cameras; an information generating apparatus that generates information for searching the images captured by the cameras; and a search apparatus that searches the images captured by the cameras. The information generating apparatus acquires the images captured by the cameras, generates retrieval data from the acquired images, and transmits the generated retrieval data to the search apparatus. The search apparatus stores the retrieval data received from the information generating apparatus in a storage device, and notifies the monitoring apparatus that the retrieval data has been stored.