Pedestrian re-identification method and system based on momentum network and comparative learning

A pedestrian re-identification and pedestrian technology, applied in the field of computer vision, to reduce costs, reduce noise interference, and improve the effect

Pending Publication Date: 2022-07-08
SUN YAT SEN UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In order to solve the above technical problems, the purpose of the present invention is to provide a pedestrian re-identification method and syste

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Pedestrian re-identification method and system based on momentum network and comparative learning
  • Pedestrian re-identification method and system based on momentum network and comparative learning
  • Pedestrian re-identification method and system based on momentum network and comparative learning

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0051]The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The numbers of the steps in the following embodiments are set only for the convenience of description, and the sequence between the steps is not limited in any way, and the execution sequence of each step in the embodiments can be adapted according to the understanding of those skilled in the art Sexual adjustment.

[0052] The invention reduces the interference of noise in the data training process by designing the momentum network, and can improve the pedestrian re-identification effect under the condition of reducing the cost of manual labeling.

[0053] refer to figure 1 and image 3 , the present invention provides a pedestrian re-identification method based on momentum network and contrastive learning, the method comprises the following steps:

[0054] S1. Obtain pedestrian images and perform labeling processing to obtain a pedest...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a pedestrian re-identification method and system based on a momentum network and comparative learning. The method comprises the following steps: obtaining a pedestrian picture and carrying out labeling processing; initializing a momentum network and a backbone network; pedestrian picture features are extracted; carrying out comparison loss calculation on the average feature set of the pedestrian pictures and updating a backbone network and a momentum network; hierarchical clustering processing is carried out on the average feature set of the pedestrian pictures, and pseudo labels are given; carrying out comparison loss calculation on a clustering result and updating a backbone network and a momentum network; updating the pedestrian picture average feature set; and iteratively optimizing the pedestrian re-identification model for multiple times, and outputting the optimized pedestrian re-identification model. According to the method, the interference of noise in the data training process is reduced by designing the momentum network, and the pedestrian re-recognition effect can be improved under the condition that the manual labeling cost is reduced. The pedestrian re-identification method and system based on the momentum network and comparative learning can be widely applied to the technical field of computer vision.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a pedestrian re-identification method and system based on momentum network and contrastive learning. Background technique [0002] With the development of deep learning, neural network technology is applied in more and more scenarios, and person re-identification, as a popular research direction in the field of computer vision, is also getting more and more attention. Person re-identification (Re-ID) is mainly To solve the problem of retrieving and matching the same pedestrian under different cameras, the final retrieval result is obtained by comparing and sorting the pedestrian image features to be queried with the pedestrian image features in the retrieval database. Pedestrian re-identification has a wide range of application scenarios and great practical significance in smart cities, security and other fields. In the process of marking pedestrian pictures, it is relatively easy ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06V20/52G06V10/762G06V10/774G06V10/80G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06N3/045G06F18/23G06F18/253G06F18/214Y02T10/40
Inventor 谢晓华胡仕腾赖剑煌
Owner SUN YAT SEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products