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Graph-based direct-push type semi-supervised pedestrian re-identification method

A pedestrian re-identification and semi-supervised technology, applied in character and pattern recognition, instruments, computer components, etc.

Pending Publication Date: 2020-04-17
西安宏规电子科技有限公司
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How to extract robust descriptors under drastic appearance changes is a technical difficulty that needs to be solved at present, so there are great limitations in the actual application process

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  • Graph-based direct-push type semi-supervised pedestrian re-identification method
  • Graph-based direct-push type semi-supervised pedestrian re-identification method
  • Graph-based direct-push type semi-supervised pedestrian re-identification method

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Embodiment Construction

[0051] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments, which are explanations of the present invention rather than limitations.

[0052] Such as figure 1 Shown is the flow logic block diagram of the present invention, and the graph-based semi-supervised pedestrian re-identification method of the present invention comprises the following steps:

[0053] Step 1: Triple construction using labeled pedestrian data;

[0054] Step 2: Train a two-channel model, such as figure 2 , get the base model;

[0055] Step 3: Use the base model to perform feature extraction on the unlabeled pedestrian data;

[0056] Step 4: Build a graph model for the extracted unlabeled pedestrian data features;

[0057] Step 5: Give the unlabeled pedestrian data pseudo-labels with confidence according to the graph model, and construct triplets for the unlabeled data;

[0058] Step 6: Fine-tune the model together using labeled...

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Abstract

The invention discloses a graph-based direct-push type semi-supervised pedestrian re-identification method, and belongs to the technical field of computer vision pedestrian re-identification. The method comprises the steps of firstly, using labeled pedestrian data for training a double-channel model; after obtaining the base model, carrying out feature extraction on the label-free pedestrian data,establishing a graph model for the extracted label-free pedestrian data features, giving a pseudo label to the label-free pedestrian data according to the graph model, and constructing a positive andnegative sample pair by using the labeled pedestrian data and the label-free pedestrian data with the pseudo label; assigning confidence coefficients to positive and negative sample pairs by using the graph model, and jointly finely adjusting the base model; gradually increasing the difficulty and confidence of positive and negative sample pairs, training the base model to complete convergence byusing a course learning method, performing feature extraction and feature matching on verification set data after a final model is obtained, and completing pedestrian re-identification according to amatching result. According to the method, the negative influence caused by wrong pseudo tags is reduced, the robustness of the model is improved, and the pedestrian re-identification precision is further improved.

Description

technical field [0001] The invention belongs to the technical field of computer vision pedestrian re-identification, and in particular relates to a graph-based transductive semi-supervised pedestrian re-identification method. Background technique [0002] Pedestrian re-identification is a technology that uses computer vision technology to determine whether a specific pedestrian exists in an image or video sequence. Widely regarded as a subproblem of image retrieval. Given a monitored pedestrian image, retrieve the pedestrian image across devices. It aims to make up for the visual limitations of the current fixed camera, and can be combined with pedestrian detection / pedestrian tracking technology, and can be widely used in intelligent video surveillance, intelligent security and other fields. Person re-identification requires the machine to recognize all images of a specific person captured by different cameras. Specifically, given a picture (query image) of a person, find...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/103G06F18/22G06F18/214G06F18/241
Inventor 常新远龚怡宏魏星洪晓鹏马智恒
Owner 西安宏规电子科技有限公司
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