Video analysis method combining target detection with human body posture estimation

Abstract

The invention relates to a video analysis method combining target detection with human body posture estimation, and the video analysis method comprises the steps: obtaining an onsite camera video stream through a streaming media server, intercepting a video frame from the onsite camera video stream, and obtaining a decoded picture; carrying out rapid target detection on each obtained picture by adopting a deep learning algorithm, and finding out target objects of all identifiable categories; judging whether a person exists or not, and sequentially carrying out dangerous behavior analysis and dangerous scene analysis on the picture; in dangerous behavior analysis and dangerous scene analysis, if a dangerous event is found, reporting and pushing an alarm to a display platform in time; and continuously analyzing the video stream in real time. According to the video analysis method, target detection and a human body posture estimation algorithm are combined and introduced into the field ofintelligent monitoring and recognition of infrastructure videos, and dangerous behaviors or scenes can be recognized, and the labor force of manual screen staring in traditional monitoring can be liberated, and the infrastructure safety management efficiency is greatly improved.

Description

technical field [0001] The invention relates to the technical field of video intelligent recognition, in particular to a video analysis method combining target detection and human body pose estimation. Background technique [0002] In power grid infrastructure projects, traditional video surveillance is based on manual screen monitoring, and random calls to monitor lines for monitoring. In the era of big data information, the number of monitoring lines is increasing rapidly, but due to the internal personnel positions and staffing of the enterprise, it is impossible for the management personnel of power grid infrastructure projects to increase significantly. Moreover, some danger sources, such as fire sources, potholes, etc., require continuous attention 24 hours a day, covering the entire construction site, which is impossible to complete manually. Therefore, there is an urgent need for automated video analysis techniques capable of dangerous behaviors and scenarios. [0...

AI Technical Summary

Problems solved by technology

At present, there are real-time and accurate algorithms, but the human body posture estimation algorithm can only analyze the personnel information, and cannot find other sources of danger in the image, let alone perform correlation analysis with other sources of danger.

[0004] It can be seen that using the existing technology for real-time video analysis in complex scenes, the mainstream target detection algorithm and human body pose estimation algorithm, due to their inherent limitations, the information obtained by each is insufficient, and many dangerous behaviors or scenes cannot be perceived and analyzed. identify

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