Video intelligent analysis technology can greatly improve the operational efficiency of video surveillance systems by filtering high-speed image data, filtering out useless information that users don't care about, and providing only useful key information, and issuing alarms and providing details. Let video surveillance change from visual interpretation to automatic interpretation. This can be said to be a qualitative industrial leap, and intelligent analysis is also the main direction of video surveillance in the future.
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Intelligent video surveillance is on the rise
However, intelligent monitoring has not been able to truly achieve universal commercial use in the past few years. The reason is that video image quality is low and it cannot provide basic resources for intelligent analysis. However, with the gradual popularization of high-definition technology, it is based on high definition. It is possible to realize intelligent analysis of images and the technology is constantly maturing.
Intelligent network camera is the main form of front-end intelligence
Front-end intelligence is one of the main application forms of video intelligent analysis technology. Network cameras and analog cameras are completely different in intelligent implementation mode due to innate factors such as hardware structure. We know that a smart camera must consist of five parts: image acquisition, camera A/D and image preprocessing, intelligent analysis and calculation, coding and compression, and network transmission. The network camera itself has image acquisition and processing, coding compression, and network transmission module. It only needs to add an intelligent analysis and calculation module to form an intelligent network camera. After the video image is analyzed and processed by the intelligent network camera, it can be transmitted to the management center according to the needs. (As shown in Figure 1), even some network cameras that are not demanding and have strong CPU performance can directly implement intelligent analysis software by implementing a series of intelligent applications.
figure 1
The analog camera is not the same, its structure is generally only the image acquisition and processing, image compression is done by DVR or other external coding equipment. In this structure, the built-in smart chip directly realizes the cost of intelligent application, so the analog camera Most of the front-end intelligence uses an external smart box. That is, the intelligent analysis box is responsible for intelligently analyzing the image information provided by the camera, and then transmitting the result to an encoding device (such as a DVR), which is then transmitted to the management center by the encoding device. That is to say, unlike the above-mentioned integrated network smart camera, the intelligentization of the analog camera must be performed by multiple independent devices. as shown in picture 2.
Although it is still common to implement smart applications through external smart boxes, this kind of split front-end intelligent solution has many devices on the one hand, and is cumbersome and costly in construction and maintenance. On the other hand, interworking between multiple devices There are also many problems such as instability in operation. In contrast, the integrated intelligent network camera based on DSP chip has obvious advantages in terms of cost investment, system security and scalability.
In addition, there is a more important point. The premise of front-end intelligence is high-quality images. The more complete and richer the intelligence, the more clear the image is needed. As mentioned in the previous article, intelligent applications must first popularize high-definition surveillance. If the analog camera wants to achieve high definition, it must transmit the video source without compression. The transmission method has both analog YPbPr component transmission and digital DVI, HDMI or HD-SDI transmission, but no matter which kind, these The cost of cables required for transmission means will be very high, and it is impossible to truly achieve universal application. The high-definition of the network camera is transmitted in a networked manner based on high-efficiency compression. The transmission cable is the network cable, which is exactly the same as the IP transmission in the standard-definition era. It does not increase the deployment cost, and the effective control of the cost. Universal application is definitely a very important factor. It can be seen that in the high-definition field, the network HD camera is inevitably the mainstream. Moreover, with the continuous maturity of network and high-definition technology, the market scale of network HD cameras has been rapidly expanding, and the models and performances are almost comparable to those of analog cameras that have been developed for many years. Accordingly, the more developed and integrated network cameras The smart front-end applications will also become more common, and the intelligent video analysis box will slowly fade out of the market.
The application of intelligent network cameras is focused
Front-end intelligence and central intelligence coexist
In contrast to front-end intelligence, which is the smart application of network cameras, another major form of intelligent applications in the field is central intelligence, also known as back-end intelligence. Different from the front-end intelligence using the front-end camera's own chip for calculation, the central intelligence is analyzed by means of the back-end computer pure software, that is, the camera does not provide any intelligent analysis and operation results, but simply transmits the image information to the management center. All intelligent operations and analysis are performed by the center. Figure 3 is a schematic diagram of the architecture of a central intelligent service.
As can be seen from the above figure, in addition to the intelligent intelligent computing software in the management center to configure the intelligent intelligent image recognition, client intelligent image recognition and third-party data analysis, the central intelligent solution is due to the front-end camera. Without any analysis of the image, all image data must be passed to the management center. Therefore, the center often needs one or more management servers with large capacity and superior performance.
Front-end intelligence and central intelligence have their own strengths
Front-end intelligence and central intelligence cause differences in application performance due to differences in architectural solutions. First of all, the front-end intelligence has three advantages in performance. First, the real-time performance is high. The camera immediately analyzes and immediately reports the collected video source, which can effectively improve the operating efficiency of the system. Second, the camera first performs video images. Analytical identification, only the abnormal images can be transmitted to the center for recording and display. These images generally only occupy a few tenths of the total image data, which can greatly reduce the pressure of the network bandwidth and ensure the efficiency of the whole system. Third, because video compression often loses part of the real information and generates some noise signals. If the system analyzes and identifies the compressed video, it will easily lead to false negatives or false positives, while the front-end intelligence is generally in the process. It is based on the collected and uncompressed original video for analysis and calculation, which effectively eliminates the above problems. However, the front-end intelligence also faces some technical defects. The most obvious is that the performance and capacity of the front-end DSP chip are dwarfed by the processing power of the back-end based on large-scale server and computer software, and the high-ends often used in some intelligent analysis. Industry, such as public security, because of the complex and diverse performance requirements of intelligence, the computational complexity of video analysis is very large, and most DSPs do not have enough memory and processing power to support, the low processing power will inevitably lead to accurate analysis. Poor sex leads to an increase in false positives. Secondly, the front-end intelligence is less scalable and flexible, that is, once the system needs to increase or decrease the number of smart cameras or adjust the position, it will be very troublesome to operate.
On the other hand, the central intelligence can achieve very perfect and excellent intelligent analysis performance with the powerful computing processing capability of the server, and it is also very convenient for scheduling and managing the front-end resources. On the other hand, as mentioned above, due to its complete dependence on the center, the system must be equipped with very good network and server resources to cope with the transmission and management of massive image data, which will definitely pose a great challenge to the construction cost. . In addition, in terms of real-time and accuracy, the central intelligent model also shows certain drawbacks.
Front-end intelligence and central intelligence applications have different focuses
First of all, the practical application of intelligent analysis is still dominated by high-end industries. Based on the characteristics of front-end intelligence and central intelligence in terms of performance, we believe that the former is more suitable for specific behavior analysis, while the central intelligence is more suitable for comprehensive behavior and Historical data analysis, this has been significant in the actual application of traffic jam control, safe city, and regulatory industry.
First, the smart application of the traffic bayonet field tends to be front-end
Preventing the reduction of road traffic violations, traffic accidents and the theft of motor vehicles is the main purpose of the construction of traffic jam monitoring system. The core performance requirements mainly include vehicle capture, license plate recognition, and face recognition. These capabilities must rely on intelligent video analytics to achieve, and this is also a relatively high-end requirement in today's intelligent analytics applications. From the perspective of smart application requirements in this field, this type of requirements are more specific and real-time, so they can be completely completed by current smart cameras.
Suzhou Keda Technology Co., Ltd. newly launched the HD smart bayonet system solution in 2011, and Figure 4 shows the framework of the system. As can be seen from the figure, the system has been heavily deployed in the front-end link, including vehicle capture, high-definition capture, etc. are typical smart applications. And, in the future, Kodak's high-definition smart bayonet system solution will continue to move from smart to back-end to front-end, which is also the mainstream trend of intelligent monitoring applications in this industry.
Second, safe city, regulatory industry is more suitable for central intelligence
Although the safe city and the regulatory industry have different expressions in the demand for intelligent monitoring applications, they can be classified into a large category. For example, Ping An City first needs to face complex monitoring sites: roads, plazas, entertainment venues, etc. Secondly, from the performance requirements, the intelligent monitoring of Safe City mainly includes personnel/item staying, behavior abnormalities, illegal gathering, perimeter invasion, etc. In addition, due to the huge amount of video resources in Ping'an City, it will inevitably be lacking in real-time monitoring. Therefore, it is more urgent to quickly analyze and call historical data. It can be seen that the intelligent monitoring of Ping'an City shows strong complexity, comprehensiveness and traceability in terms of location and performance requirements, which puts higher requirements on the platform carrying intelligent computing. As far as the processing power of smart camera chips is concerned, it is still relatively stubborn. Moreover, the complexity of the monitoring site also determines that the system must have strong flexibility and scalability in the front-end link, which is also the disadvantage of the front-end intelligence mentioned above.
The same is true for prisons, detention centers, etc. Although the monitoring system of the regulatory industry does not have complex sites, the diversified needs of illegal gathering of people, abnormal behavior, and illegal detention also show a series of complex and comprehensive characteristics. Therefore, from the current actual case, it is obviously more important to adopt the central intelligent solution.
Of course, no matter from the technical characteristics or the characteristics of the market demand, the front-end intelligence and the central intelligence are not contradictory or even mutually complementary and complement each other. A video surveillance system often does not have one or the other, but must be the front-end and The center is smart and uses. Even in the future, with the continuous improvement of chip technology processing capabilities and the continuous improvement of intelligent algorithms, the market prospects of intelligent network cameras have been greatly improved. I believe that the two will coexist and the situation will be the same.
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