Action recognition method and device

An action recognition and action technology, applied in the field of action recognition, can solve the problems of high algorithm time complexity, large memory, and more time, and achieve the effect of reducing computational complexity, reducing memory loss, and improving speed.

Active Publication Date: 2018-09-28
GUANGDONG UNIV OF TECH
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  • Description
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AI Technical Summary

Problems solved by technology

When performing action recognition based on the above algorithm, in order to ensure the accuracy of judgment, the time complexity of the algorithm will be high, so it will take more time and consume a lot of memory to realize action recognition, resulting in lower efficiency of action recognition

Method used

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  • Action recognition method and device

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Embodiment Construction

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0053] In order to enable those skilled in the art to better understand the solution of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0054]Next, an action recognition method provided by an embodiment of the present invention is introduced in detail. figure 1 It is a flow chart of an action recognition method provided by an embodim...

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Abstract

The embodiment of the invention discloses an action recognition method and device. The method comprises the following steps that: utilizing a fuzzy feature extraction algorithm to extract a corresponding gesture vector from a video to be tested; utilizing a K-means clustering algorithm to carry out clustering analysis on the gesture vector to obtain a discretized action vector; and inquiring a pre-established action recognition model to determine an action type corresponding to the action vector. A fuzzy feature is applied for extraction to improve feature extraction speed through a K-means clustering processing way. On the basis of a minimum deviation algorithm of an approximate core extreme learning machine, an action recognition model is established, calculation complexity is lowered, and operation storage loss is reduced under a situation that high accuracy is kept. In addition, when action recognition is carried out, the action recognition model is directly inquired to determine the action type corresponding to the action vector, and action recognition efficiency is greatly improved.

Description

technical field [0001] The invention relates to the technical field of video monitoring, in particular to a method and device for motion recognition. Background technique [0002] With the development of artificial intelligence, the application of motion recognition technology is becoming more and more extensive, for example, human-computer interaction, augmented reality (Augmented Reality, AR), and intelligent visual surveillance. Taking intelligent visual monitoring as an example, it uses computer vision technology to process, analyze and understand video signals, and without human intervention, through automatic analysis of sequence images to locate, identify and track changes in the monitoring scene, On this basis, it can analyze and judge the behavior of the target object, and can issue an alarm or provide useful information in time when an abnormal situation occurs, effectively assisting security personnel to deal with crises, and minimizing false alarms and missed ala...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/20G06V20/41G06F18/23213
Inventor 曾铭宇刘波肖燕珊
Owner GUANGDONG UNIV OF TECH
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