Intelligent video analysis applications can be broadly divided into *law enforcement and security, literature and art, and tobacco industry. 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 the detection of relics. Wenbo class focuses on the protection of objects and personnel. Surveillance can prevent objects from being lost, take away, pick up alarms, and carry out retrograde monitoring on special channels. It can also monitor the number of people and personnel density; tobacco industry applications are biased in behavioral analysis, such as detection of remnants in prohibited areas. , combined with the special performance of production equipment failures to detect faults. HD smart and non-HD smart use the same principle in the underlying algorithm. HD algorithms need to provide more computing power for analysis. At present, the behavior analysis class adopts CIF resolution. When the input is a high-definition video, the pixel is cropped and then analyzed. For the pattern recognition class, high-definition video is used for analysis to obtain more accurate results.
The requirements for video surveillance in different industries generally have very obvious differences, especially for the application requirements of intelligent video analysis technology, which also determines the specificity of the types of detection behavior and abnormal events among different industries. For example, in a safe city, it is possible to develop behavior analysis functions such as fights, robbery, and climb over in response to urban security emergencies. In the bank's ATM self-service area, behavior analysis functions such as illegally pasting small paper strips, installing fake keyboards, masking, and violent robbery can be realized through the analysis of current crimes in ATM self-service areas. In the transportation industry, more functions can be implemented to alert traffic incidents such as retrograde, illegal parking, and traffic jams. Only by combining the practical applications of the industry and in-depth understanding of the specific issues of different industries, can we better grasp the needs of users and put the functions of intelligent video analysis technology into practice. This is also the ultimate reflection of the future industrial value of intelligent video analysis technology. .
For smart video analytics solutions, different industries have different focuses. Taking prisons as an example, in order to prevent prisoners from escaping from prisons and gang fights, the demand for the perimeter and the concentration of people is relatively prominent, mainly to solve the problems in these two areas, and for some airports and other public places where mobility is relatively large. It said that the demand for the detection and detection of abandoned objects is relatively prominent to prevent the explosion of dangerous goods and suspicious persons committing 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 perimeter of its security needs are relatively high, once it is close to the need to cause warnings, the defense needs of the perimeter is more prominent.
For video surveillance, the clearer the image, the more detailed the details, the better the viewing experience, and the higher the accuracy of application services such as smart, so image resolution is the eternal pursuit of video surveillance. In the past, the low definition of video has made it difficult for surveillance personnel to find valuable clues. The use of high-definition video technology has provided us with high-definition, high-quality video sources that contain rich and complete information, thereby improving the intelligent analysis of video. The accuracy rate avoids the loss of information due to scene problems. From this perspective, the intelligent analysis of video is based on high-definition, so the requirements of intelligent video analysis for front-end camera definition are relatively high, and high-definition means that the storage pressure increases, and accordingly, the back-end storage device The stability and capacity also have certain requirements.
There is not much difference between HD monitoring intelligent video analysis and non-HD intelligent video analysis technology, but the results are completely different. HD monitoring can improve the efficiency of intelligent video analysis, and can obtain more and more effective information from the video. For example, face and license plate recognition require more detail in the image, which can increase the recognition rate while providing more convincing pictures and videos.
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