Pedestrian Reidentification Algorithm Based on Local Feature Fusion Mechanism

In the application of pedestrian reidentification, misjudgment is often caused by low video resolution, illumination variation, and background interference. In order to solve these problems, this study proposes a pedestrian reidentification algorithm based on local feature fusion. Taking advantage o...

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Bibliographic Details
Published inJournal of Electrical and Computer Engineering Vol. 2022; pp. 1 - 10
Main Author Liu, Xiaobing
Format Journal Article
LanguageEnglish
Published New York Hindawi 19.05.2022
John Wiley & Sons, Inc
Wiley
Subjects
Algorithms
Deep learning
Design
Distance measurement
Feature extraction
Interference
Methods
Neural networks
Object recognition
Pedestrians
Regions
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Summary:In the application of pedestrian reidentification, misjudgment is often caused by low video resolution, illumination variation, and background interference. In order to solve these problems, this study proposes a pedestrian reidentification algorithm based on local feature fusion. Taking advantage of the inherent structure of the human body, we pay attention to pedestrian parts with prominent features and ignore other parts with interference information. Feature extraction is carried out for detected pedestrian parts with significant features, and new fusion features are generated. By calculating distance measurement between image features, pedestrians are classified and recognized. Experimental results show that the accuracy of the proposed algorithm is superior to that of other comparison algorithms on the datasets of Market1501, Duke, and CUHK03. It is proved that the proposed algorithm has a good pedestrian reidentification effect.
Bibliography:ObjectType-Article-1
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ISSN:2090-0147
2090-0155
DOI:10.1155/2022/3490919