High-altitude parabolic trajectory discrimination method, device and equipment and storage medium

Abstract

The embodiment of the invention provides a high-altitude parabolic trajectory discrimination method and device, equipment and a storage medium, and relates to the technical field of images. The high-altitude parabolic trajectory discrimination method comprises the following steps: receiving video stream data, and processing the video stream data according to a frame difference method to obtain a connected domain; creating nodes according to the connected domain to obtain a node graph list; calculating the distance between the nodes according to a preset distance calculation formula, and updating the node graph list; pruning and deleting the nodes in the node graph list according to a preset condition; traversing the pruned and deleted node graph list at an interval of a preset frame number, and determining a parabolic trajectory according to the node graph list. The high-altitude parabolic trajectory discrimination method can monitor the high-altitude parabolic event in real time, can discriminate the motion trajectory of the parabolic object, and has the technical effects of high operation speed and strong robustness.

Description

technical field [0001] This application relates to the field of image technology, in particular, to a method, device, equipment, and storage medium for discriminating high-altitude parabolic trajectories. Background technique [0002] At present, high-altitude throwing objects is a relatively common uncivilized phenomenon in cities. This kind of behavior of throwing debris from windows or rooftops of buildings can pollute the environment and sanitation in light cases, and cause serious injuries or even fatal consequences in severe cases. Therefore, many areas will parabolic as a crime. [0003] In the prior art, the traditional high-altitude parabolic supervision method is mainly to retrieve the surveillance video of the time period after the parabolic event occurs for manual screening. This method is not only time-consuming and labor-intensive, but also may cause missing inspections or video data to be cleaned up, making it difficult to be held accountable for accidents. ...

AI Technical Summary

Problems solved by technology

However, such monitoring methods based on technologies such as millimeter-wave radar, sensors, radio signals, and deep learning have problems such as time-consuming calculations, expensive equipment maintenance, and large data requirements.

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