Intelligent video monitoring system based on deep learning

Abstract

The invention discloses an intelligent video monitoring system based on deep learning, and relates to the field of computers. The intelligent video monitoring system based on deep learning comprises an image acquisition preprocessing module, a pedestrian detection module, a pedestrian tracking module, a pedestrian analysis module and a client module. The image acquisition preprocessing module is used for providing input image data for the system and preprocessing an image. And the pedestrian detection module is used for calibrating the human body of the acquired image and returning the mass center position coordinates of the human body. And the pedestrian tracking module is used for tracking pedestrians and generating a tracking track. And the pedestrian analysis module is used for judgingthe acquired data according to an abnormal behavior judgment rule. And the client module is used for displaying a real-time monitoring picture and displaying a detection result. Related ideas and algorithm models in deep learning are utilized to realize 'intellectualization' of video monitoring.

Description

technical field [0001] The invention relates to the field of computers, in particular to an intelligent video monitoring system based on deep learning. Background technique [0002] At present, video surveillance generally has the problem of "only recording but not judging", that is, only recording and saving the monitoring picture, but not able to timely judge and detect the abnormal behavior that may appear in the video. When abnormal behavior occurs, it needs to rely on a lot of manpower and material resources to analyze and judge the video content. Since people's attention cannot be concentrated for a long time, it is easy to cause missed detection or false detection of important information in the video when using manual analysis. With the rapid development of science and technology, various video devices are gradually popularized, and the number of videos shows an exponential growth trend. It is difficult for traditional methods to perform effective analysis in this s...

AI Technical Summary

Problems solved by technology

Since people's attention cannot be concentrated for a long time, it is easy to miss or misdetect important information in the video when using manual analysis

With the rapid development of science and technology, various video devices are gradually popularized, and the number of videos shows an exponential growth trend. It is difficult for traditional methods to carry out effective analysis in this case.

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