Sample Problems in Person Re-Identification

Hua Han, Mengchu Zhou

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Person Re-Identification (Re-ID) is a new technology that has emerged in the field of intelligent video analysis in recent years. It belongs to the category of image processing and analysis in complex video environments. Person Re-ID faces the problem of fast and low-cost learning in the case of small samples. In recent years, many research results have emerged regarding the problem of small-sample learning in person Re-ID. New training samples generated by Cycle-GAN can be used to alleviate the problem of data imbalance in pedestrian Re-ID. Person Re-ID technology can be used to obtain customer's behavior trajectory, obtain customer's digital information, help businesses mine more commercial value, and provide customers with customized services. In addition to the application in offline retail solutions, Re-ID can be used to connect online and offline retail scenarios and provide a “one-stop” consumer service experience.

Original languageEnglish (US)
Title of host publicationIntelligent Image and Video Analytics
Subtitle of host publicationClustering and Classification Applications
PublisherCRC Press
Pages303-330
Number of pages28
ISBN (Electronic)9781000851908
ISBN (Print)9780367512989
DOIs
StatePublished - Jan 1 2023

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Engineering

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