Moving track prediction method based on big data

Abstract

The invention discloses a big data-based moving track prediction method, which is suitable for predicting whether a pedestrian enters a warning area, and comprises the following steps: step 1, based on a hypergraph neural network, carrying out target identification on the pedestrian in an obtained video frame image; 2, when it is judged that the recognized pedestrian enters the early warning area from the image collection area, the moving track of the pedestrian is predicted according to the moving speed and the moving direction of the pedestrian in the video frame image, and the outer side of the warning area is sequentially divided into the early warning area and the image collection area; and 3, when it is judged that the predicted moving track of the pedestrian enters the warning area, safety warning information is generated and sent. According to the technical scheme of the invention, the method achieves the prediction of the movement track of the pedestrian, reduces the calculation amount of an intelligent security and protection monitoring system for pedestrian data, provides a basis for the judgment of a mistaken entry behavior, and improves the early warning reliability of the intelligent security and protection monitoring system.

Description

technical field [0001] The present application relates to the technical field of data processing, in particular, to a method for predicting movement trajectory based on big data. Background technique [0002] In the field of intelligent security monitoring, it is usually based on camera and image recognition technology to monitor, identify, and warn pedestrians in the monitoring area to provide corresponding security services. [0003] In the prior art, most of the intelligent security monitoring systems are usually a passive trigger monitoring system. Only when pedestrians enter the early warning area will they monitor and identify pedestrians entering the area, resulting in the need to monitor and identify the early warning area. A large amount of pedestrian data is processed, which occupies a large amount of data processing resources. [0004] Moreover, there is also the problem of being unable to identify pedestrians who have entered the early warning area by mistake, a...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, most of the intelligent security monitoring systems are usually a passive trigger monitoring system. Only when pedestrians enter the early warning area will they monitor and identify pedestrians entering the area, resulting in the need to monitor and identify the early warning area. A large amount of pedestrian data is processed, which occupies a large amount of data processing resources

[0004] In addition, there is still the problem of being unable to identify pedestrians who stray into the early warning area, and it is impossible to provide a basis for the judgment of pedestrians' deliberate behavior and strayed behavior, resulting in low reliability and accuracy of early warning information

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