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Method and device for labeling abnormal behaviors

A behavioral and abnormal technology, applied in the field of labeling abnormal behaviors, can solve the problems of manpower consumption and time-consuming

Pending Publication Date: 2020-09-15
EZHOU INST OF IND TECH HUAZHONG UNIV OF SCI & TECH +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The existing technology usually uses manual labeling when labeling abnormal behavior data sets, which will not only take a lot of time, but also consume a lot of manpower

Method used

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  • Method and device for labeling abnormal behaviors
  • Method and device for labeling abnormal behaviors
  • Method and device for labeling abnormal behaviors

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Embodiment Construction

[0075] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0076] The first embodiment of the present invention provides a method for marking abnormal behavior, such as figure 1 As shown, the method includes:

[0077] Step 101: Based on the current abnormal behavior data set, pre-train the neural network to obtain the first neural network model.

[0078] Step 102: Copy all the network architecture and model parameters except the output layer in the first neural network model to create a s...

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Abstract

The invention relates to the technical field of behavior analysis, in particular to a method and device for labeling abnormal behaviors. The method comprises the steps of pre-training a neural networkbased on a current abnormal behavior data set to obtain a first neural network model; copying all network architectures and model parameters except the output layer in the first neural network model,and creating a second neural network model; adding an output layer of which the tensor size corresponds to the number of abnormal behavior detection categories into the second neural network model; training the second neural network model added with the output layer according to a target data set obtained by labeling in a PASCAL VOC labeling mode or a COCO labeling mode to obtain an abnormal behavior labeling model; inputting the to-be-annotated data set into the abnormal behavior annotation model, and annotating each piece of to-be-annotated data in the to-be-annotated data set to obtain anannotated data set; judging whether the labeled data set is correctly labeled or not; and inputting the data with wrong annotations into the abnormal behavior annotation model for re-annotation.

Description

technical field [0001] The invention relates to the technical field of behavior analysis, in particular to a method and device for marking abnormal behavior. Background technique [0002] Abnormal behavior detection is an important branch of human behavior recognition and an important research task in the field of computer vision. Abnormal behavior detection mainly refers to the classification and detection of specific behaviors. Specific behaviors can be fights and stampedes in public places. The abnormal behavior detection process mainly includes two parts: target feature extraction and feature classification. Target feature extraction refers to extracting features that can represent abnormal behaviors from video data. Feature classification refers to classifying the extracted features, for example, classifying the extracted feature vectors through a support vector machine (Support Vector Machine, SVM). [0003] With the development of deep learning in the field of comp...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/04G06N3/08G06Q10/10
CPCG06N3/08G06Q10/10G06N3/045G06F18/2411G06F18/214
Inventor 莫益军刘金阳
Owner EZHOU INST OF IND TECH HUAZHONG UNIV OF SCI & TECH
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