Video-based re-identification method and system for people in smoke scene and terminal

A re-identification and video technology, applied in the field of person recognition, can solve the problems of not being able to complete end-to-end discrimination well, and the accuracy of person re-identification being poor.

Active Publication Date: 2021-01-05
GUANGDONG UNIV OF PETROCHEMICAL TECH
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0005] The existing technology cannot complete the end-to-end discrimination very well, and the accuracy of person re-identification is poor

Method used

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  • Video-based re-identification method and system for people in smoke scene and terminal
  • Video-based re-identification method and system for people in smoke scene and terminal
  • Video-based re-identification method and system for people in smoke scene and terminal

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Embodiment

[0129]The structure diagram of the human re-identification network based on the video-based smoke scene of the present invention is as followsFigure 5 As shown, the specific implementation is as follows:

[0130]In step 1, a symmetrical non-local codec K estimation network is established for video defogging, and the specific steps are as follows:

[0131]Step 1.1, establish a non-local residual block. Based on the success of the residual network and the non-local neural network, the present invention combines them to construct a non-local residual block. Each non-local residual block is composed of a typical residual unit, an up-sampling layer and a non-local block. Its specific structure is as followsimage 3 Represents (non-local residual block), the non-local residual block is used as the encoder and decoder to establish the coding structure and the decoding structure.

[0132]Step 1.2, establish an RNN layer to learn the temporal consistency information contained in adjacent frames of eac...

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Abstract

The invention belongs to the technical field of character recognition, and discloses a video-based re-identification method and system for people in a smoke scene and a terminal; and the method comprises the steps: constructing a symmetric non-local coding and decoding K estimation network model to carry out defogging of a video; constructing a discrimination network model, and estimating whetherthe input video is a normal video or a fog-free video generated by a defogging sub-network based on the constructed discrimination network model; and constructing a non-local double-attention character re-identification sub-network model, and re-identifying the character. According to the invention, the problem of difficult re-identification caused by foggy re-identification of people in the videocan be solved. According to the invention, people re-identification can be well completed in a foggy video. The whole process of the method is an end-to-end design, and the method can be used more simply. The method is a technology for re-identifying the person in the smoke scene based on the video, end-to-end judgment can be completed, and re-identification of the person can be well completed.

Description

Technical field[0001]The invention belongs to the technical field of person recognition, and in particular relates to a method, system and terminal for re-identifying people in a video-based smoke scene.Background technique[0002]Currently, video-based personnel then identify key tasks for many safety-critical applications, such as automatic video surveillance and forensics. The task of video-based portrait recognition is to match portraits from a large number of portraits. It has been extensively researched in recent years, but this task is still challenging because of the low quality of the video of the people taken, the change of posture, the angle of view of the camera and the messy background.[0003]The presence of haze, fog, smoke and other small particles in the air will scatter the light in the atmosphere, thereby greatly reducing the visibility of human images or videos. These fuzzy people lose contrast and color fidelity. People can also observe that in these haze portrait f...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/44G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/10G06V10/34G06N3/045G06F18/24
Inventor 荆晓远程立姚永芳孔晓辉王许辉黄鹤
Owner GUANGDONG UNIV OF PETROCHEMICAL TECH
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