Intelligent video surveillance system implementation and development characteristics
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Intelligent video surveillance is based on digital, network video surveillance, but it is different from general network video surveillance. It is a higher-end video surveillance application. The intelligent video surveillance system can automatically identify different objects, detect abnormal conditions in the monitoring screen, and can provide alarms and provide useful information in the fastest and best way possible, which can more effectively assist the security personnel in handling crisis and maximize Reduce false positives and false negatives.
Intelligent video surveillance concept
Intelligent Video Surveillance (IVS Intelligent Video Surveillance) is based on computer vision technology to analyze the video content of surveillance scenes, extract key information in the scene, and form monitoring methods for corresponding events and alarms. It is a new generation surveillance system based on video content analysis. Intelligent video surveillance technology uses computer's powerful data processing functions to perform high-speed analysis on massive data in video frames, filter out information that users don't care about, and only provide useful key information for the monitor.
Intelligent video surveillance system features
1) Perimeter alert and intrusion detection: Accurately detect and recognize the movement of a single object or multiple objects in complex weather conditions (such as rain, snow, fog, high wind, etc.) and perform motion trajectory tracking, including the direction of movement , sports characteristics, etc.;
2) Items are stolen or detected; when the objects in the monitoring scene are stolen and moved, the algorithm will automatically detect such actions and is often used for the monitoring of valuables and key equipment;
3) Detection of legacy or abandoned items: When an object (such as a box, package, vehicle, person, etc.) stays in a sensitive area for too long, or exceeds a predefined length of time, an alarm is generated. Typical application scenarios include airports, train stations, subway stations, etc.
4) Traffic statistics: Count the number of people or objects crossing the entrance or the designated area. For example, for the owner to count the number of patrons visiting his shop on a certain day;
5) crowd detection; identify the overall movement characteristics of the crowd, including speed, direction, etc., to avoid the formation of congestion, or timely detection of abnormal conditions. Typical application scenarios include places where people gather at supermarkets, train stations, etc.
6) PTZ tracking; after detecting a moving object, automatically send PTZ control instructions according to the motion of the object so that the camera can automatically track the object. After the object exceeds the monitoring range of the camera, it automatically informs the camera in the area where the object is located to continue tracking. ;
7) Fireworks detection: According to the time-space characteristics of pyrotechnics in the process of fire, real-time detection of pyrotechnics is performed;
8) Human behavior analysis: Based on the target detection and classification, the human body's various behavioral characteristics are used to describe and analyze various behaviors, and what dangers and potentially dangerous behaviors are extracted, such as fighting, snatching, and suddenly inverting. Land and other behavior;
9) Face recognition: automatic detection and recognition of the character's facial features, and identification or verification of the identity of the character through comparison with database files;
10) Vehicle identification: Identify the characteristics of the vehicle's shape, color, license plate number, etc., and feed it back to the monitor.
Such applications can be used in scenarios such as stolen vehicle tracking.
Several ways of current intelligent video implementation
The network video monitoring system is based on the computer network architecture. The network camera or encoder is the front-end access device. The network monitoring and management platform is a video monitoring system that monitors and manages core devices, PC clients and decoders as back-end browsing devices. The implementation of intelligent video functions based on network video surveillance systems can be divided into the following ways:
1, server-side smart applications
The so-called server-side intelligence refers to a dedicated intelligent video analysis server that imports one or more video images from a network monitoring system or a monitoring platform. The intelligent video analysis server sets intelligent rules for these images. When a smart alarm is generated, it can be itself Carry out relevant business alarms or related alarm linkage services by reporting to the network monitoring platform. In this way, video intelligent services are applied. The front end and the platform of the monitoring system are only responsible for dispatching the image resources required for intelligent video analysis to the intelligent video analysis server without any intelligent analysis work. The pressure of the front-end coding equipment is very small. In addition, because of flexible scheduling of image resources from the network monitoring system, the deployment of intelligent video services will be more flexible and can be deployed at any point in the monitoring system at any time, so that any network monitoring system can achieve video intelligence through simple system interconnection. Change.
In a large-scale monitoring system, if the server-side intelligent mode exerts great pressure on the back-end management resources, it needs to be relieved by improving the performance of back-end devices, such as increasing the server configuration and increasing the number of servers. From the current general experience, a quad-core high-performance CPU can handle 16-channel CIF quality smart analysis applications.
2, video encoder DVS (or DVR) front-end intelligence
The so-called front-end intelligence refers to the direct intelligent analysis of video information through the front-end network video equipment to implement corresponding intelligent video functions. In this kind of system, the front-end camera often analyzes the captured video through the embedded video analysis service, and utilizes the powerful DSP chip processing capability of the embedded system itself. While processing the codec, it also uses DSP's extra processing resources. Implement intelligent video analysis. This approach will become more and more a mainstream approach to video intelligence applications as the front-end DSP processing capabilities increase.
The front-end intelligence is deployed at a fixed front-end point that requires intelligent analysis, has strong specificity and stable performance, and is a core access method for future video intelligent monitoring services.
3, front-end, back-end combination of implementation
This is a compromise, and it is also a reasonable and balanced intelligent video implementation. On the one hand, full use of the excess CPU resources of the front-end network video equipment to achieve some simple intelligent video functions, on the other hand, the back-end video software is focused on resources to achieve higher-level or more application-oriented intelligent video functions, such as license plate recognition, Behavior identification and so on. In such a system, the pressure of smart video is more evenly distributed on the front-end network video equipment and the back-end management server. Each equipment performs its own duty and the system architecture is more reasonable. The current front-end DSP processing chip capability cannot support a complete intelligent analysis service, it is also a good way.
Intelligent Video Analysis System Brings New Business Feature Feature 1: Effectively Improves Video Alarm Accuracy
The intelligent video surveillance system can use the features and characteristics of the extracted “intelligent analysis technology†from a variety of complex image frames to correctly identify the rules of different objects and their trajectory, and it can clearly distinguish people, vehicles or other objects.
Filter out natural disturbances such as water waves, tides, leaves, light and shadow, and light changes, especially in situations where previous motion detection methods cannot be implemented and applied (such as detecting whether there are past ships on the water, etc.), once the monitoring screen is found. When the "key target" appears, the system can provide useful information or alarms in the quickest and best way. Therefore, the information sent from the "Intelligent Video Analysis" system must be valid or truly in violation of the security rules. The information must also be real information that must be processed in time. It will effectively increase the accuracy of the alarm and expand the application range of the video alarm.
From the principle of analysis, the discriminating mechanism of intelligent video analysis usually includes the following points:
1. Extract effective content: In any case, the amount of important information will be much lower than the amount of background information. For example, static information such as ground and buildings, as well as dynamic information such as wind, water, rain, snow, and tree shadows, can be “smart videoâ€. The "analysis" system judgment belongs to the background information, and the important information is the information of people, cars and other activities, which will be separated from the background first, eliminating those useless background information.
2. Object Attribute Recognition: The intelligent video analysis software has an "object analysis engine" that can accurately identify people, animals, vehicles, or other objects based on the size, speed, and motion of different activity targets and successfully separate important information. come out.
3. Object behavior analysis: The intelligent video analysis system software has configurable security rules, which can compare various types of activity goals obtained through analysis with the established security rules. For example: set the "virtual" security margin in the area specified in the image. Once it is identified that the "target object" crosses this safety margin, the system will activate the alarm and prompt the monitoring personnel to pay attention or handle the alarm.
Feature two, monitoring new ways
With the increasing demand for video surveillance and the rationalization of front-end camera prices, the number of camera installations in a system has also increased exponentially. Large video channels and large-scale monitoring centers have brought great work pressure to control managers, demanding one. It is unrealistic for the (or several) monitoring staff to look at the images of dozens of hundreds of roads at any time and then to judge whether there are any abnormalities in each screen. This will greatly reduce the safety and effectiveness of the monitoring system and the actual operation and management capabilities. Therefore, The video surveillance market needs a disruptive technology and a revolutionary concept. The “Intelligent Video Analysis†technology is humanized, intelligent, and refined to extract real information, significantly reduce false alarms, and more effectively assist security personnel in prevention and handling. Crisis events and effective weapons to effectively contain all types of crimes. The "Intelligent Video Analysis" system allows users to more accurately define the characteristics of security threats. Multiple virtual alert lines or guarded areas can be set within the scope of image surveillance. To set up and analyze different important objects, truly only violating the police Rules of conduct only generate efficient monitoring alarms.
Intelligent video surveillance technology will accelerate the replacement of analog video by digital video. With the adoption of the "Intelligent Video Analysis" system, the monitoring performance will be further improved. The traditional (central control room) centralized monitoring model will also gradually shift to distribution. In monitoring mode, security personnel will be freed from boring screen observations, no longer stick to the traditional monitoring room, and devote themselves to places closer to the surveillance and action scenes, and the “intelligent video analysis†system will automatically transmit suspicious information to security personnel. The location information of the target more quickly handles the situation on the site and meets the needs of long-term monitoring and rapid response to "anti-terrorism." It can be predicted that the intelligent monitoring system will quickly integrate into various types of security control systems in the wake of the tumultuous changes in the monitoring model. Important role.
Truly "preventive" capability features III. Really "preventive" capabilities
How to anticipate crimes in advance and take timely and proper measures to protect people and property safety has become an increasingly urgent need for video surveillance systems. Intelligent video analysis monitoring system's "determination of legacy items", "remaining area cues", "moving direction discrimination", etc. The function will enable security personnel to perceive abnormal behaviors in advance and focus on the corresponding monitoring areas, identify potential threats as early as possible, and make coping strategies. For example, some people leave suspicious objects in public places or people stay for long periods of time near sensitive areas. , Intelligent video analysis system will be able to identify this behavior, prompt to the security personnel, to achieve early warning of possible crimes or violations.
Feature 4: Effectively expand the use of video resources
The results of intelligent video analysis for security systems can also be used to link high-speed dome cameras for tracking photography or related intelligent services for linked platforms. When suspicious targets touch multiple intelligent video analysis areas of multiple cameras, the system will It can drive high-speed dome cameras to continuously track suspicious targets. When multiple suspicious targets are encountered together, they can also capture their own moving images to make the monitoring system more intelligent.
Whether it is a traditional video surveillance system or a network video surveillance system, the video images it monitors are generally only used in the security surveillance field. In an intelligent video analysis system, these image resources can also have more uses. For example: to count the number of people appearing on the video screen, to provide reference data for “passenger trafficâ€; to detect the status of vehicles driving on the road, as statistical data on traffic flow; to actively identify violations, illegal parking, and road accidents, Give tips; automatically identify VIP users in shopping malls, prompt customer service personnel to proactively provide quality services, and so on.
Conclusion
Intelligentization, digitization and networking are inevitable trends in the development of video surveillance. The emergence of intelligent video surveillance is a direct reflection of this trend. Intelligent video surveillance equipment has more powerful image processing capabilities and intelligence factors than ordinary network video surveillance equipment, so it can provide users with more advanced video analysis capabilities, it can greatly improve the capabilities of video surveillance systems, and make video Resources can play a greater role. In order to promote the development of the intelligent video industry and achieve a multi-win-win situation, it is necessary to properly organize the monitoring equipment hardware suppliers, intelligent video software vendors, distributors and distributors, and system integrators, so that they can fully Give full play to their respective advantages and create a comprehensive solution that meets the needs of end users.