The invention discloses an aAbnormal behavior detection method based on a space-time automatic encoder

A technology of automatic encoder and detection method, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of large influence, poor detection effect, limited precision, etc., and achieve the effect of preventing damage

Active Publication Date: 2019-04-12
JILIN UNIV
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Problems solved by technology

[0004] In unsupervised learning, human body motion information is estimated only by image RGB information. This method is greatly affected by light and shadow, and the accuracy is limited in crowded places. When there

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  • The invention discloses an aAbnormal behavior detection method based on a space-time automatic encoder
  • The invention discloses an aAbnormal behavior detection method based on a space-time automatic encoder
  • The invention discloses an aAbnormal behavior detection method based on a space-time automatic encoder

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[0051] The implementation process of the present invention will be further described below in conjunction with the accompanying drawings, so that those skilled in the art can better understand the present invention.

[0052] A spatio-temporal autoencoder abnormal behavior detection method that integrates multimodal feature information, including constructing a training sample image library in advance, such as figure 1 As shown, the method includes the following steps:

[0053] 1. Create a surveillance video data set and preprocess the video, such as image 3 As shown, it specifically includes the following steps:

[0054] 1.1 Divide all videos into a training set and a test set, of which the training set accounts for 80%, and the test set accounts for 20%. The training set only contains positive sample videos, and the test set contains positive sample and negative sample videos;

[0055] 1.2 Preprocessing: convert the video streams in the training set and the test set into f...

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Abstract

The invention discloses an abnormal behavior detection method based on a space-time automatic encoder, and belongs to the technical field of image processing and mode recognition. The method comprisesthe steps of firstly obtaining a video image of a to-be-detected area; i; inputting the optical flow information and the RGB information of the video into a space-time auto-encoder respectively; p; passing through a 3D convolution layer in an automatic encoder; a; a pooling layer, an LSTM layer and a deconvolution layer, DERIVING RECONSTRUCTION INFORMATION, T, the method comprises the steps thatinput information is compared with reconstructed information, abnormal scores are obtained according to an abnormal scoring formula, t, then the two abnormal scores are fused to obtain a comprehensiveabnormal score, t, the comprehensive abnormal score is compared with a threshold value, whether abnormal behaviors exist or not and the occurrence time of abnormal conditions are judged, and the higher the abnormal score is, t, the higher the probability of occurrence of the abnormal conditions is. According to the invention, t, through the space-time automatic encoder fusing multi-modal input information, abnormal behaviors in crowds are detected in public areas such as banks, and early warning is sent to security personnel, so that emergencies such as major abnormal events are reduced.

Description

technical field [0001] The invention belongs to the technical field of image processing and pattern recognition, and in particular relates to a method for detecting abnormal behavior based on a spatio-temporal automatic encoder. Background technique [0002] In recent years, violations of important public places such as the banking and financial industries have occurred from time to time in my country by different means, causing varying degrees of loss and injury to state property and people's lives. Starting from this, abnormal behavior detection in public places has become a research hotspot in the current security prevention and control system, and more and more experts and scholars are devoted to this field. [0003] To solve this problem, researchers have proposed a variety of abnormal behavior monitoring methods, which can be roughly divided into traditional methods, supervised learning methods and unsupervised learning methods according to different methods. Traditio...

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Application Information

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IPC IPC(8): G06K9/62G06K9/46
CPCG06V10/56G06F18/214
Inventor 王世刚岳海纯韦健赵岩
Owner JILIN UNIV
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