At present, the intelligent video function of the network video system is mainly realized by means of center analysis. That is, through the video analysis software of the back-end server, the video stream uploaded by the front-end camera is intelligently analyzed, and the intelligent processing of the front-end video information is realized. What we are talking about today is "intelligent pre-positioning" in relation to the handling of such centralized servers.
With the development of network video surveillance, the advantages of video digitization have become increasingly apparent. As a digital terminal, the camera not only has the functions of digital video capture and recording, but also can perform some relatively high-end video analysis and processing through the CPU embedded in the network camera. The so-called "smart front-end" is to embed the video analysis function or other management functions and intelligent functions that need to be processed into the camera, the so-called "use of cameras to do intelligent video analysis and processing."
The special feature of the “Intelligent Front†function network camera is that it is based on an open platform and can embed more intelligent analysis applications into the front-end network cameras to meet the personalized intelligent video surveillance needs of users. This also means the same network. Cameras can be differentiated by embedding different smart pre-applications.
Intelligent front-end is to move the video analysis function to the front-end for processing. On the one hand, it can save background resources and allow each camera to process video independently, so that intelligent video analysis has better accuracy and better scalability. Upgrade capability.
The author believes that the future direction of development is to handle the video from the front-end and pass the preliminary analysis results to the background, and the background will take corresponding alarm measures according to the results. These measures may be to activate a video or sound and light alarm, send text messages, e-mail and so on. The back end will not need to perform video processing or video analysis, but only accept the corresponding processing results, and then take corresponding linkage measures based on this result. Therefore, the future is a development process in which the front-end and back-end are closely integrated with each other.
In addition, in today's irresistible trend of network monitoring and intelligent development, we need more resources for open, shared vendors, the development of camera-side CPU resources open, allowing more third-party professional video analysis software to write to the camera, Integrate the strengths and advantages of each company to work together, giving customers more choice.
Intelligent analysis is equivalent to giving the "monitor" to video surveillance. It is the future development trend. Smart front-end will also develop rapidly under the trend of intelligent video surveillance development and promote the development of the entire intelligent video surveillance. The author summarizes the advantages of intelligent front-end as follows:
Saving network bandwidth to process webcam video in the background requires the video to be transmitted to a back-end server, and then processed and analyzed according to the video content. In this case, it is easy to waste a lot of bandwidth on unnecessary video transmission, but also for system storage. Certain pressure.
The front-end video analysis function puts some analysis work into the front-end to handle. After discovering the situation, the analysis results are then transmitted to the background. The resources or processing pressure of the entire system is balanced and the network bandwidth is reduced.
Increased scalability Each chip and intelligent software in the smart front camera can run independently with the camera and have independent video analysis capabilities. In a video surveillance system, Smart Front Cameras can be deployed at the right place at any time to achieve intelligent function expansion without significantly increasing the burden on the server for the background.
More accurate false positives are problems that need to be overcome in the development of intelligent network monitoring, and have nothing to do with intelligent front or rear placement. However, if the camera obtains video data, if it is transmitted through the network to the background, the network delay, packet loss, or errors caused by compression in the process may affect the accuracy of the analysis. Front-end intelligence performs intelligent video analysis directly in the camera, enabling more accurate video processing.
Although current intelligent video analysis does not achieve 100% accuracy, it can at least help users solve some very practical problems. For example, the front-end can distinguish the alarm state from the video under normal conditions to help the customer quickly retrieve the current situation. This kind of video analysis technology is moving towards a higher speed and intelligence.
Cost savings in the back-end server to achieve intelligence and does not say that the network (transmission media and equipment) requirements are high, but also requires a lot of servers to achieve analysis and processing, will produce a large number of hardware and software in the system configuration and maintenance Service cost. The front-end camera resources are opened up to realize intelligent front-end and video processing functions can be moved forward without increasing the cost. On the contrary, a server can handle up to 20 to 30 such video analysis functions. If some analysis processing is moved to the front end, the server only needs to handle alarms, which will also save the configuration cost of a large number of background servers.
In addition, intelligent analysis software itself is more expensive. In the future, if more hardware and software vendors develop cooperatively in a more open manner, more third-party video analysis software engineers will inevitably join the R&D of this platform, adding more intelligent analysis functions to the camera. More extensive intelligent analysis capabilities. With flexible video analytics module applications, the overall cost of intelligent video analytics can be reduced.
Smart front-end application is the development trend After adopting the “Intelligent Front-end†application, corresponding intelligent analysis can be performed at the front end, and only the results after the analysis and processing are transmitted to the back-end platform. For example, if a network camera is used to monitor whether suspicious persons pass through the surveillance area, if background server analysis is used, the video needs to be transmitted to the background every moment to enable intelligent analysis. However, if the front-end camera has intelligent analysis functions, although the camera is monitoring the entrance at all times, in the normal state, no data is transmitted to the background. Only when the front end analyzes someone entering and leaving, the camera will automatically analyze the intelligence. The video is transmitted to the background. If there is only one person in and out of the day for more than ten minutes a day, then the camera does not need to transmit video data at other times, which can greatly reduce the amount of data transmission and reduce the pressure of network transmission.
At present, the camera end can also be attached with a local SD card or other storage device. When network congestion, network failures or other emergencies occur, images can be stored directly on the storage device attached to the camera. Therefore, it is not necessary to absolutely rely on network transmission. This can reduce the burden on the network and avoid bursty networks. The event affects the storage of information. The analysis of the direct front-end camera processing is less restricted by other factors, and the impact on security is also much smaller.
The opening of chip resources is the key to development. Openness is the most significant feature of the network video surveillance era. With the improvement of the chip performance of the camera, more chip resources will be opened up. Some intelligent video companies that specialize in video analysis can be based on openness. The chip resources, the corresponding program embedded in the camera, can better help achieve front-end intelligence. By then, not only the camera's external interface is open, but the network protocol involved in the camera is also open. It can be compatible with more third-party video analysis software, and it is more convenient to choose the best combination among many hardware and software manufacturers.
Smart front-end can also be understood as the application platform of the network camera. The future network camera not only plays the role of basic video acquisition and transmission, but also can run third-party video analysis software. For example, the most popular iPhones currently running can run many APP applications, and there are also many program services tailored to a specific group of people. These program services make iPhones not only exist as a communication tool. The same is true for network cameras. In the future, not only video will be transmitted, but also embedded in various software applications. Some customized intelligent analysis functions can be run on the camera side. Therefore, with the development of network cameras, the front-end smart development must be based on a more open application platform.
With the development of network video surveillance, the advantages of video digitization have become increasingly apparent. As a digital terminal, the camera not only has the functions of digital video capture and recording, but also can perform some relatively high-end video analysis and processing through the CPU embedded in the network camera. The so-called "smart front-end" is to embed the video analysis function or other management functions and intelligent functions that need to be processed into the camera, the so-called "use of cameras to do intelligent video analysis and processing."
The special feature of the “Intelligent Front†function network camera is that it is based on an open platform and can embed more intelligent analysis applications into the front-end network cameras to meet the personalized intelligent video surveillance needs of users. This also means the same network. Cameras can be differentiated by embedding different smart pre-applications.
Intelligent front-end is to move the video analysis function to the front-end for processing. On the one hand, it can save background resources and allow each camera to process video independently, so that intelligent video analysis has better accuracy and better scalability. Upgrade capability.
The author believes that the future direction of development is to handle the video from the front-end and pass the preliminary analysis results to the background, and the background will take corresponding alarm measures according to the results. These measures may be to activate a video or sound and light alarm, send text messages, e-mail and so on. The back end will not need to perform video processing or video analysis, but only accept the corresponding processing results, and then take corresponding linkage measures based on this result. Therefore, the future is a development process in which the front-end and back-end are closely integrated with each other.
In addition, in today's irresistible trend of network monitoring and intelligent development, we need more resources for open, shared vendors, the development of camera-side CPU resources open, allowing more third-party professional video analysis software to write to the camera, Integrate the strengths and advantages of each company to work together, giving customers more choice.
Intelligent analysis is equivalent to giving the "monitor" to video surveillance. It is the future development trend. Smart front-end will also develop rapidly under the trend of intelligent video surveillance development and promote the development of the entire intelligent video surveillance. The author summarizes the advantages of intelligent front-end as follows:
Saving network bandwidth to process webcam video in the background requires the video to be transmitted to a back-end server, and then processed and analyzed according to the video content. In this case, it is easy to waste a lot of bandwidth on unnecessary video transmission, but also for system storage. Certain pressure.
The front-end video analysis function puts some analysis work into the front-end to handle. After discovering the situation, the analysis results are then transmitted to the background. The resources or processing pressure of the entire system is balanced and the network bandwidth is reduced.
Increased scalability Each chip and intelligent software in the smart front camera can run independently with the camera and have independent video analysis capabilities. In a video surveillance system, Smart Front Cameras can be deployed at the right place at any time to achieve intelligent function expansion without significantly increasing the burden on the server for the background.
More accurate false positives are problems that need to be overcome in the development of intelligent network monitoring, and have nothing to do with intelligent front or rear placement. However, if the camera obtains video data, if it is transmitted through the network to the background, the network delay, packet loss, or errors caused by compression in the process may affect the accuracy of the analysis. Front-end intelligence performs intelligent video analysis directly in the camera, enabling more accurate video processing.
Although current intelligent video analysis does not achieve 100% accuracy, it can at least help users solve some very practical problems. For example, the front-end can distinguish the alarm state from the video under normal conditions to help the customer quickly retrieve the current situation. This kind of video analysis technology is moving towards a higher speed and intelligence.
Cost savings in the back-end server to achieve intelligence and does not say that the network (transmission media and equipment) requirements are high, but also requires a lot of servers to achieve analysis and processing, will produce a large number of hardware and software in the system configuration and maintenance Service cost. The front-end camera resources are opened up to realize intelligent front-end and video processing functions can be moved forward without increasing the cost. On the contrary, a server can handle up to 20 to 30 such video analysis functions. If some analysis processing is moved to the front end, the server only needs to handle alarms, which will also save the configuration cost of a large number of background servers.
In addition, intelligent analysis software itself is more expensive. In the future, if more hardware and software vendors develop cooperatively in a more open manner, more third-party video analysis software engineers will inevitably join the R&D of this platform, adding more intelligent analysis functions to the camera. More extensive intelligent analysis capabilities. With flexible video analytics module applications, the overall cost of intelligent video analytics can be reduced.
Smart front-end application is the development trend After adopting the “Intelligent Front-end†application, corresponding intelligent analysis can be performed at the front end, and only the results after the analysis and processing are transmitted to the back-end platform. For example, if a network camera is used to monitor whether suspicious persons pass through the surveillance area, if background server analysis is used, the video needs to be transmitted to the background every moment to enable intelligent analysis. However, if the front-end camera has intelligent analysis functions, although the camera is monitoring the entrance at all times, in the normal state, no data is transmitted to the background. Only when the front end analyzes someone entering and leaving, the camera will automatically analyze the intelligence. The video is transmitted to the background. If there is only one person in and out of the day for more than ten minutes a day, then the camera does not need to transmit video data at other times, which can greatly reduce the amount of data transmission and reduce the pressure of network transmission.
At present, the camera end can also be attached with a local SD card or other storage device. When network congestion, network failures or other emergencies occur, images can be stored directly on the storage device attached to the camera. Therefore, it is not necessary to absolutely rely on network transmission. This can reduce the burden on the network and avoid bursty networks. The event affects the storage of information. The analysis of the direct front-end camera processing is less restricted by other factors, and the impact on security is also much smaller.
The opening of chip resources is the key to development. Openness is the most significant feature of the network video surveillance era. With the improvement of the chip performance of the camera, more chip resources will be opened up. Some intelligent video companies that specialize in video analysis can be based on openness. The chip resources, the corresponding program embedded in the camera, can better help achieve front-end intelligence. By then, not only the camera's external interface is open, but the network protocol involved in the camera is also open. It can be compatible with more third-party video analysis software, and it is more convenient to choose the best combination among many hardware and software manufacturers.
Smart front-end can also be understood as the application platform of the network camera. The future network camera not only plays the role of basic video acquisition and transmission, but also can run third-party video analysis software. For example, the most popular iPhones currently running can run many APP applications, and there are also many program services tailored to a specific group of people. These program services make iPhones not only exist as a communication tool. The same is true for network cameras. In the future, not only video will be transmitted, but also embedded in various software applications. Some customized intelligent analysis functions can be run on the camera side. Therefore, with the development of network cameras, the front-end smart development must be based on a more open application platform.
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