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A Pedestrian Re-Identification Method to Solve Misalignment of Components

A pedestrian re-identification, pedestrian technology, applied in the field of machine learning and computer vision, which can solve problems such as component misalignment

Active Publication Date: 2022-05-17
NANJING UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a pedestrian re-identification method to solve component misalignment, so as to solve the problem of component misalignment existing in the technology of pedestrian re-identification method based on the depth model of components at the present stage

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  • A Pedestrian Re-Identification Method to Solve Misalignment of Components
  • A Pedestrian Re-Identification Method to Solve Misalignment of Components

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Embodiment Construction

[0077] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0078] The embodiment of the present invention discloses a pedestrian re-identification method to solve the misalignment of components. This method is applied to quickly analyze the monitoring video data of public safety places, and automatically find specific pedestrians, which can significantly improve the quality of monitoring, and is of great importance to urban construction and social security. meaning.

[0079] Such as figure 1 As shown, it is a schematic workflow diagram of a pedestrian re-identification method for solving component misalignment provided in the embodiment of the present invention. This embodiment discloses a pedestrian re-identification method for solving component misalignment, including:

[0080]Step 1. ...

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Abstract

The invention discloses a pedestrian re-identification method for solving component misalignment. That is to construct a deep representation of pedestrian images, extract multi-layer features through the backbone network model, use sub-modules to enhance and fuse multi-layer features, form a multi-branch structure, extract component features and global features of each branch; train the constructed network model, Define the configuration related to the experiment, optimize the model parameters of the network model; pedestrian re-identification, extract the deep representation of the query image through the trained network model, and use the second paradigm to normalize according to the similarity between each query image and the query set, Returns the recognition results for each query image. The best person re-identification performance at this stage is achieved by the person re-identification method based on the fusion of multi-scale features to solve the misalignment of parts.

Description

technical field [0001] The invention relates to the fields of machine learning and computer vision, in particular to a method for solving the problem of component misalignment. Background technique [0002] With the development of modern society, public safety has gradually attracted people's attention. Shopping malls, apartments, schools, hospitals, office buildings, large plazas and other places with dense crowds and prone to public safety incidents have installed a large number of surveillance camera systems. The research on surveillance video is mainly reflected in the identification of visible objects, especially is pedestrian recognition. This is because pedestrians are generally the target of surveillance systems. More precisely, the task of the surveillance system is to search for a specific pedestrian in the surveillance video data, that is, the task of pedestrian re-identification. [0003] However, on the one hand, the data volume of surveillance video is often...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V40/10G06V10/80G06V10/764G06V10/774G06V10/82G06K9/62G06T5/00G06T7/55G06N3/04G06N3/08
CPCG06T5/003G06T7/55G06N3/084G06T2207/20081G06T2207/20084G06T2207/30196G06V40/103G06N3/045G06F18/241G06F18/253G06F18/214
Inventor 杨育彬林喜鹏
Owner NANJING UNIV
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