Operator data processing method and system

Abstract

The invention discloses an operator data processing method, which comprises the following steps of obtaining a target track point of a target user from operator data; performing simplification processing on the target track point to obtain a first simplified moving track point; calculating the first simplified moving track point by using a neighborhood algorithm to obtain an influence region; filtering and matching the track point in the total operator data by using the influence range to obtain the matching track point in the influence range; dividing the matched track points belonging to thesame user to be under the same user; performing simplification processing on the matched track points under each user to obtain a second simplified moving track point; performing similarity matchingoperation on the first simplified moving track point and the second simplified moving track point to obtain the matching result. The method has the advantages that the defects of the conventional modecan be overcome; the accuracy and the applicability are high; the powerful basis is provided for the criminal case detection. Meanwhile, the invention also provides an operator data processing systemwith the beneficial effects.

Description

technical field [0001] The present application relates to the technical field of data processing, in particular to a method and system for processing operator data. Background technique [0002] In modern society, in order to fully protect the personal safety and property of ordinary citizens, how to detect criminal suspects in time, and further determine whether there are accomplices and other targets based on the criminal suspect’s track is to improve the city’s security level and solve cases in a timely manner. important research directions. [0003] In the prior art, the simplest method of manual tracking or the use of cameras deployed in various places is usually used to determine the trajectory of the target person, and then manually combine and screen the trajectory of the target person with similar characteristics in each video recording. It not only consumes a lot of manpower and material resources, but also has extremely low efficiency and poor real-time performan...

AI Technical Summary

Problems solved by technology

It not only consumes a lot of manpower and material resources, but also has extremely low efficiency and poor real-time performance. It is only suitable for the detection of cases in a fixed and small physical area, and is not suitable for the trajectory identification and tracking of target persons in a large area, long distance or even across provinces.

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