Multi-scale convolution feature fusion pedestrian re-identification method based on pose embedding

A technology of pedestrian re-identification and feature fusion, which is applied in the field of pedestrian re-identification based on multi-scale convolutional feature fusion based on pose embedding, which can solve the problem of low accuracy of pedestrian re-identification.

Pending Publication Date: 2021-09-10
XIAN UNIV OF TECH
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Problems solved by technology

[0004] The purpose of the present invention is to provide a multi-scale convolution feature fusion pedestrian re-identification method based on pose embedding, which solv

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  • Multi-scale convolution feature fusion pedestrian re-identification method based on pose embedding
  • Multi-scale convolution feature fusion pedestrian re-identification method based on pose embedding
  • Multi-scale convolution feature fusion pedestrian re-identification method based on pose embedding

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Embodiment Construction

[0035] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0036] A person re-identification method based on multi-scale convolutional feature fusion based on pose embedding, such as figure 1 shown, including the following steps:

[0037] Step 1. Establish an image database. In this embodiment, the image database consists of pedestrian images collected manually and corrected by a computer, with a total of 72,000 images. The original pedestrian image is preprocessed by random erasing to obtain the pedestrian image, and the Resnet-50 network model is optimized for the baseline network, and the pedestrian image is input into the optimized Resnet-50 network model to obtain the deep convolution feature;

[0038] Step 1.1, using the random erasing enhancement processing method to randomly erase the original pedestrian image to obtain the pedestrian image;

[0039] Specifically, Random Erasing Augmentatio...

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Abstract

The invention discloses a multi-scale convolution feature fusion pedestrian re-identification method based on pose embedding, and the method comprises the steps: carrying out the preprocessing of an original pedestrian image through a random erasing mode, obtaining a pedestrian image, carrying out the baseline network optimization of a Resnet-50 network model, and extracting deep convolution features; extracting a saliency human body image from the original pedestrian image; performing posture extraction on the human body saliency image, and then extracting local semantic features from the body part image; carrying out weighted fusion on the deep convolution features and the local semantic features, carrying out distance measurement on weighted fusion features, and generating an initial measurement list; and reordering the images in the initial measurement list according to a reordering algorithm to obtain an image correct matching ranking, and outputting a pedestrian matching image to identify a specific pedestrian. The identification and positioning precision can be greatly improved.

Description

technical field [0001] The invention belongs to the technical field of image processing methods, and relates to a multi-scale convolution feature fusion pedestrian re-identification method based on pose embedding. Background technique [0002] In recent years, artificial intelligence, as an important point of progress in the development of science and technology, has come out on top among all the technologies we use. Its use in the field of intelligent surveillance has also become extremely important. With the expansion of the city, the monitoring system is further popularized, and there are thousands of cameras all over the streets and alleys in every city. The use of cameras is increasing, and the cost of monitoring alone is extremely expensive, and it is impossible to monitor so many images at the same time. Therefore, pedestrian re-identification technology has attracted the attention of researchers. It can help people to monitor, track, and identify pedestrians. Hum...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/253
Inventor 廖开阳雷浩郑元林章明珠范冰黄港
Owner XIAN UNIV OF TECH
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