For a long time, intelligent video surveillance has only been a demonstration product used to demonstrate strength in the security field. The only mass-produced intelligent video surveillance products are not only low-yield but also expensive, and limited by performance, which is basically not practical. In recent years, with the improvement of hardware processing capabilities and price reduction, as well as the development of computer processing technology, intelligent video surveillance products have gradually entered the stage of large-scale development from the demonstration stage, which has become one of the hot topics in the security industry. Large manufacturers have invested a lot of manpower and resources in research and development, and video intelligent monitoring is considered by the industry to be a revolutionary technology that dominates network monitoring.
With the gradual prevalence of high-definition network monitoring, the drawbacks of high-storage and high-bandwidth have gradually become the biggest shortcomings in surveillance systems. The selection of useful value monitoring mode has become the main demand. Imagine the collection of still images for many years. Video has no value at all. Intelligent and selective acquisition is the key factor to save bandwidth and save storage. Therefore, the demand for intelligent video surveillance in the industry has increased with time. Nowadays, the monitoring system that we are exposed to every day, whether it is analog or analog-digital mixing, or pure digital, still works as “real-time monitoring, real-time video recordingâ€, which not only wastes manpower, but also wastes material resources and faces countless Video recording, it is difficult to extract some valuable video, long-term preservation is also a big problem. In addition, the existing monitoring system is very dependent on people's participation. Intelligent monitoring can share human resources and save resources. Therefore, intelligent video surveillance is a development trend. It is also the only way to develop video surveillance systems.
What are the advantages of monitoring intelligent analysis technology?In the current monitoring system, storage and transmission problems are the primary difficulties. A large amount of useless video information is stored and transmitted, which wastes storage space and increases bandwidth. The purpose of intelligent analysis is to reduce the space required for video storage and thus alleviate bandwidth. Pressure, or for some useless video, use low-stream streaming to compress or transmit, which is more convenient for the whole system to investigate or query, and improve the application value of the monitoring system.
At present, intelligent monitoring technologies mainly include: identification, trajectory identification, and environmental judgment compensation identification. Identification includes face recognition, license plate number recognition, vehicle type identification, vessel identification, traffic light recognition, and the like. The most critical requirement for the intelligent monitoring technology of the identification class is that the accuracy of the identification is better than 98%, so that it can better meet the needs of most monitoring customers. This is the more common intelligent analysis purpose. The trajectory identification mainly includes virtual warning line, virtual warning area, intelligent tracking, number of people statistics, traffic statistics, appearance and disappearance of objects, sudden running of personnel, sudden gathering of personnel, etc.; environmental judgment compensation mainly includes rain, snow, fog, etc. Bad weather, low night illumination, camera occlusion or offset, camera shake, etc. Intelligent monitoring technology enables more normal monitoring in a harsh video environment. When the video affected by the environment is unclear, the person in the picture is found early, or the alarm is detected after the camera is offset. Such functions have universal adaptability, and most monitoring points have potential requirements.
What is the implementation of intelligent video surveillance?At present, there are two ways to implement intelligent video surveillance, one is front-end intelligent analysis; the other is back-end intelligent analysis. The biggest difference between the two intelligent analysis methods is that the former uses the chip of the front-end camera itself for calculation, while the latter uses the software of the back-end computer for analysis. However, whether it is the front-end embedded or the back-end software mode, the implementation of its functions is completed by analyzing the video signal through the operation of the developed core algorithm program. The difference between embedded and pure software is that the computing platform is different. The former can complete the operation of the core algorithm and related calculations on the camera DSP chip; the pure software-based computing platform is a general-purpose computer.
Intelligent video surveillance analysis: choose front end or back end?Judging from the current use of intelligent monitoring and analysis, the vast majority of the applications are still back-end analysis mode, which is convenient for troubleshooting, and can effectively solve the pressure of storage capacity. However, because it is back-end analysis, the network needs to transmit video signals. The network bandwidth requirements are relatively high, and this is precisely the problem that cannot be properly solved at present; the benefits of front-end intelligent analysis can solve the transmission problem brought by the back-end analysis, but the current environment, the front-end DSP chip and the latter The processing power of the end computer is really limited. Many video analysis operations are very large. Most DSPs do not have enough memory and processing power to implement effective operation. The reduced processing power will result in low analysis accuracy and lead to increased false positives. .
However, with the enhancement of computing power of embedded systems and the improvement of intelligent video analysis algorithms, it will become a trend to embed video analysis modules in front-end devices such as video servers and network cameras. The advantage of doing video intelligent analysis on the front end is that the real-time performance is high, and only the useful alarm information and pictures are transmitted to the background, which can greatly reduce the amount of data transmitted and reduce the burden of background storage.
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