A mobile trajectory prediction method based on big data

Abstract

The present application discloses a moving trajectory prediction method based on big data. The method is suitable for predicting whether a pedestrian will enter a warning area. The moving trajectory prediction method includes: step 1, based on a hypergraph neural network, for the obtained video frame. Target recognition of pedestrians in the image; Step 2, when it is determined that the identified pedestrian enters the early warning area from the image acquisition area, the movement trajectory of the pedestrian is predicted according to the movement speed and movement direction of the pedestrian in the video frame image, wherein, The outer side of the warning area is divided into an early warning area and an image collection area in turn; in step 3, when it is determined that the predicted movement trajectory of the pedestrian enters the warning area, a safety warning message is generated and sent. Through the technical solution in the present application, the movement trajectory of pedestrians is predicted, the calculation amount of pedestrian data by the intelligent security monitoring system is reduced, the basis for the judgment of wrong entry behavior is provided, and the reliability of the early warning of the intelligent security monitoring system is improved.

Description

technical field [0001] The present application relates to the technical field of data processing, and 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 passively triggered monitoring systems. Only when pedestrians enter the early warning area, will the pedestrians entering the area be monitored and identified, resulting in the need to monitor and identify the early warning area. It takes up a lot of data processing resources for processing a large amount of pedestrian data. [0004] In addition, there is also the problem of inability to identify pedestrians who have entered the warning area by mistake, and ...

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

Images