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Action recognition method, terminal and storage medium

A motion recognition and action technology, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve the problem that blurred video clips cannot be correctly recognized, and achieve the effect of improving reliability and ensuring accuracy

Pending Publication Date: 2022-04-15
SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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  • Claims
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AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides an action recognition method, terminal and storage medium to solve the problem that the existing weakly supervised action positioning method can only identify the most recognizable action and background segments in the video, and a large number of blurred video segments cannot be correctly identified question

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  • Action recognition method, terminal and storage medium
  • Action recognition method, terminal and storage medium

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Embodiment Construction

[0026] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

[0027] It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude one or more other features. , whole, step, operation, element, component and / or the presence or addition of a collection thereof.

[0028] It shou...

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Abstract

The invention is suitable for the technical field of machine vision, and provides an action recognition method, a terminal and a storage medium, and the method comprises the steps: obtaining the feature vector representation of a target video; determining an attention weight of a foreground image frame in the target video according to a preset attention dynamic threshold, wherein the attention weight is used for indicating a probability that the image frame contains an action; obtaining a target feature vector according to the attention weight of the foreground image frame and the feature vector representation; and inputting the target feature vector into an action recognition network for action recognition to obtain an action recognition result in the target video. According to the scheme, the reliability of image action recognition can be improved, and the accuracy of a video action recognition result is ensured.

Description

technical field [0001] The present application belongs to the technical field of machine vision, and in particular relates to an action recognition method, a terminal and a storage medium. Background technique [0002] With the rapid growth of the number of videos, computer vision technology has received extensive attention from researchers. The technology of extracting frames with actions from uncropped videos to achieve action positioning tasks has a wide range of applications in video surveillance, automatic driving, video description, video search, human-computer interaction, automatic sports commentary, patient monitoring, etc. . [0003] For the existing technology, the action localization method with strong supervision has made great progress, but it needs to manually mark each action and the time of each action, which is very time-consuming and laborious, and it is difficult to apply to most realistic scenarios. Therefore, a weakly supervised method has emerged. W...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V40/20G06V20/40G06N3/08G06N3/04G06V10/82
Inventor 闫浩张锲石程俊
Owner SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI
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