Universal Flying: Intelligent Video Analysis Algorithm Becomes Mainstream

The intelligent video analysis algorithm is a computer image visual analysis technology. It analyzes the background and objects in the scene and tracks the objects that appear in the scene. According to the video analysis function, users can preset different alarm rules in different scenarios. Whenever there is a behavior that violates predefined rules in the scene, the system will automatically issue an alarm, and the front-mounted smart camera will automatically Upload the alarm image to the back-end monitoring PC so that the user can take relevant measures.

Now, with the enhancement of the computing power of embedded systems and the improvement of intelligent video analysis algorithms, it has 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 at the front end is high real-time performance, and only useful alarm screens are transmitted to the background. This can greatly reduce the amount of data transmission and reduce the network occupancy pressure, and can also reduce the burden of background storage.

Front-end intelligent analysis embeds the video analysis function into the front-end network camera DSP chip to realize the intelligent function, while the back-end intelligence uses the software-only software to analyze. However, whether it is front-end embedded or back-end pure software, its function is achieved through the analysis of the video signal through the operation of the intelligent core algorithm program.

No matter from theory or from technology, analog video signal will lose some real information and generate some noise signal after A/D conversion and video compression. So the intelligent software analysis system will compress the video if it is post-compressed. The analysis and processing of the video will produce more leak alarms or false alarms.

Some intelligent camera solutions now prepend the intelligent software analysis system before video compression processing. That is, such intelligent network cameras perform target extraction and analysis processing on uncompressed original images, which in spite of analyzing and processing more video information. However, it is obvious that better analysis and processing results can be obtained, and the occurrence of missing alarms or false alarms can be significantly reduced. In addition, it only needs to send related videos to the back end for monitoring and recording in the event of an abnormality. Therefore, only a very small amount of data information needs to be transmitted via the network. The traffic of these data information cannot be calculated according to statistics. 1/50 of the total video traffic, which greatly reduces the network bandwidth requirements and consumption, reducing the user's investment in the network, while at the same time the user is not very good network conditions also brought the use of intelligent video network monitoring system may.

Based on smart camera video analysis, in general, compared to the PC-based intelligent video analysis system, the computing performance is slightly inferior. Therefore, it is required to optimize and improve the image processing algorithm and its DSP performance of the smart camera under the condition that the basic performance remains unchanged, so as to fit the embedded requirements in the smart camera.

However, with the enhancement of the 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 in the front-end is not only real-time, high accuracy of analysis, but only useful information transmitted to the back-end, which not only greatly reduces the amount of data transmission, but also reduces the burden of background storage.

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