Tags: Smart Video Video Surveillance HD Video
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At present, intelligent video analytics technology has received more and more attention from the security community. Many projects have begun to apply intelligent video analytics.
The development trend of intelligent video analysis technology
From the product form of the intelligent analysis system, it is divided into two categories, one is realized by intelligent algorithm + DSP, which is commonly used in intelligent analysis cameras and intelligent analysis video servers installed at the front end. At present, there are many systems using this method, which is to put the software and hardware with intelligent analysis function on the video collection end. In a conventional video surveillance system, video occupies a large amount of storage space and transmission bandwidth. How to solve these problems is the primary difficulty. A large amount of useless video information is stored and transmitted, which wastes both storage space and bandwidth. The purpose of intelligent analysis is to alleviate the space required for video storage and the bandwidth pressure required for transmission, or low for some unimportant videos. The stream is compressed and transmitted. In this way, it is more helpful to enhance the application value of the monitoring system. The algorithm processing is implemented by the front end, and the service pressure of the back end is very small, so that a large number of intelligent analysis cameras can be configured in one system.
The other is the operating mode of the back-end PC server plus intelligent analysis software, such as Aimetis and iOmniscient. In this way, because it is processed by the back-end PC server, it is better than the processing of the front-end intelligent analysis camera in terms of processing performance. Since the algorithm takes up a lot of hardware resources, when processing multiple analyses at the same time, the system Insufficient processing power is manifested. Because the back-end PC server has powerful analytical processing capabilities (compared to the front-end DSP+ software approach), PC server processing is often used in very important intelligent analysis scenarios.
From the main application of intelligent analysis, there are two major development directions. The first is the intelligent identification technology represented by license plate recognition and face recognition, which is mainly used in electronic police, machine Yang and customs.
The other is behavior analysis technology represented by rules such as perimeter prevention, population statistics, automatic tracking, retrograde, and ban. It is mainly applied to the surrounding perimeter warning zone, shopping malls, traffic, scenic spot traffic statistics, road no-stop, Violation of rules, scene tracking and other aspects.
1. Dual-machine automatic tracking: intelligent analysis camera plus ordinary fastball mode. Can be applied to urban police emergency plans. Object tracking of emergencies.
2. Human traffic statistics: The number of personnel entering and leaving the statistical box selection area is applied to the analysis and statistics of customer traffic in supermarkets, helping merchants to formulate corresponding sales strategies. It is applied to attractions and subway stations to provide traffic data for personnel control applications.
3. Crossing the warning zone: detect the perimeter by setting a virtual fence. When a suspicious person or object is found to cross the fence, an alarm is triggered and the alarm signal is uploaded to the monitoring management center. At the same time, the alarm screen can be uploaded to the remote monitoring user via the network. It is applied to traffic crosswalks or zebra crossings, fences in key areas of factories, schools, guard walls and so on.
4. Loss analysis: By drawing an area on the monitoring screen where important items are placed as a warning area, as long as the item leaves the warning area, the alarm rule will be triggered immediately. It is used in key protected areas such as museums, exhibition halls, auctions, gold and silver shops.
5. Direction analysis: In actual monitoring, people may care about the direction of the flow of people and the direction of movement of the vehicle. Through the identification of the direction, it can be judged whether the target is illegally moving or driving. If reverse behavior occurs, the target will be automatically locked. And at the same time alarm. It is used in one-way roads; important entrances and exits, etc.
6. Intelligent tracking: target the suspicious person or object, record the movement track of the target, and the camera will follow the target rotation and alarm. It is applied to high-end residential areas, personnel forbidden areas, confidential areas, and important protection areas. And as a case, the trajectory of the case playback process is analyzed. Achieve the role of rapid resolution.
The intelligent video analysis system solves the problem of security personnel getting rid of the complicated and boring "screen-to-screen" task, which is done by the device; the other is to quickly search from the massive video data to the image that you want to find. Studies have shown that the operator will miss 90% of the video information after staring at the TV wall for more than 10 minutes, making the work meaningless. Often the monitoring system becomes the basis for tracing the event afterwards. But the intelligent video analytics system turns after-the-fact forensics into an active defense, enabling the project to achieve the most effective security at the most cost-effective. Intelligent video analysis systems have played a pivotal role in the successful application of all kinds of industries.
Application of intelligent video analysis technology
So, what are the different demand characteristics of different industries in intelligent video? What is the difference between intelligent video analysis of high-definition surveillance and non-HD intelligent video analysis technology? What are the requirements for equipment?
Intelligent video analysis applications can be broadly divided into public security law enforcement and security, cultural and literary, and tobacco industries. Law enforcement will focus more on pattern recognition, such as license plate recognition and face recognition; security will focus on retrograde monitoring, illegal intrusion, crowd gathering, slipping, and detection of remnants; Wenbo focuses on item care and personnel safety. Monitoring, object loss, removal, alarm, and retrograde monitoring of special channels, as well as statistics and personnel density monitoring; tobacco industry applications biased behavior analysis, such as detection of remnants in prohibited areas , combined with the special performance of production equipment failure for fault detection. High-definition intelligence and non-HD intelligence use the same principles in the underlying algorithms. HD algorithms need to provide more computing power for analysis. At present, the behavior analysis class, using CIF resolution is enough, when the input is high-definition video, the pixels will be cut and then analyzed; for the pattern recognition class, high-definition video is used for analysis to obtain more accurate results.
As far as the intelligent video analysis function can be realized, almost all applications are mainly aimed at people, vehicles and objects. Beijing Wen'an is divided into three categories according to the specific application: 1. Public safety prevention. It includes tracking of target movement trajectory, target movement range, target movement direction, special human behavior, monitoring of special vehicle behavior, etc. It is characterized by timely warning of suspicious abnormal events. 2. Data statistics analysis class. Typical examples are passenger flow statistics and traffic statistics applications. This type of application is relatively independent, with data output as the final result, and more to provide different types of data reports to assist management decisions. 3. Intelligent traffic monitoring. Typical examples include license plate recognition, red light illegal monitoring, and traffic comprehensive illegal monitoring. This type of application is mainly for vehicle analysis, relatively mature, and application cases are more common.
In addition, Beijing Wen'an combined with the status quo of domestic video surveillance, and targeted development of a special application for video image quality itself, to monitor the signal quality of each video image, the appearance of video images Video camera loss, snowflake, scrolling, blur, color cast, picture freeze, gain imbalance and other common camera faults make accurate judgments, help users to find the video quality fault of the front-end camera in time, effectively control the operation of the front-end equipment, and ensure the normal monitoring system. run.
The demand for video surveillance in different industries generally has very obvious differences, especially for the application requirements of intelligent video analysis technology, which also determines the particularity of detection behavior types and abnormal events between different industries. For example, in a safe city, it can specifically develop behavioral analysis functions such as fighting, robbery, and climbing for urban public security emergencies. In the ATM self-service area of ​​the bank, through the analysis of the current ATM self-service area crime means, behavior analysis functions such as illegally pasting small notes, installing fake keyboards, masking, and violent robbery can be realized. In the transportation industry, more functions can be realized for traffic events such as retrograde, illegal parking, traffic congestion and the like. Only by combining the actual application of the industry and understanding the specific problems of different industries, can we better grasp the needs of users and implement the functions of intelligent video analysis technology to the actual application, which is the ultimate embodiment of the future industrialization value of intelligent video analysis technology. .
Different industries have different focuses on solutions for intelligent video analytics. Taking prisons as an example, in order to prevent prisoners from jailbreaking and mass gangs, the demand for perimeters and crowds is more prominent, mainly to solve these two problems, and for some airports and other public places where mobility is relatively large. It is said that the need for the detection of defects and the detection of defects are more prominent, in order to prevent the explosion of dangerous goods and suspicious persons to commit crimes.
For nuclear power plants, oil fields, power grids and other places, generally in remote areas, the flow of people is not large, but the safety and security requirements of its perimeter are relatively high. Once someone approaches, it needs to be alerted, and the defense demand for the perimeter is more prominent.
For video surveillance, the clearer the image, the more obvious the details, the better the viewing experience, and the higher the accuracy of application services such as smart, so image clarity is the eternal pursuit of video surveillance. In the past, video clarity was low, which made it difficult for monitors to find valuable clues. The use of high-definition video technology provided us with high-definition, high-quality video sources with rich and complete information, thus improving the intelligent analysis of video. Accuracy, avoiding the loss of information due to scene problems. In this respect, the intelligent analysis of video is based on high-definition, so the requirements of intelligent video analysis for front-end camera clarity are relatively high, high-definition means increased storage pressure, correspondingly, to the back-end storage device There are also certain requirements for stability and capacity.
There is not much difference between HD surveillance intelligent video analysis and non-HD intelligent video analysis technology, but the results are completely different. High-definition surveillance can improve the efficiency of intelligent video analysis, while getting more and more effective information from the video. For example, face and license plate recognition requires more detail in the image, which can improve the recognition rate while providing more convincing pictures and videos.
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