SoMem: a self-optimizing memory network for distributed person re-identification

Jianming Lv, Chaojie Hu, Yipeng Zhou, Xiaojun Chen

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

Person Re-Identification (Re-ID) aims to match the persons contained in surveillance videos, and is usually run on powerful servers in a supervised mode. However, centralized processing of massive video from thousands of cameras in a city is very costly and causes serious problems of privacy protection. Moreover, the labeling of numerous data for supervised training is also infeasible in this scenario. To address this problem, we propose a novel Self-optimizing Memory Network model, namely SoMem, which runs person Re-ID on edge devices in a totally unsupervised and distributed way. Specifically, SoMem adopts a random walk based collaborative training procedure to optimize the visual model on each camera based on locally collected images, and builds a distributed memory network to memorize and match the observed persons by using a distributed mutual ranking algorithm. Based on the cross-camera person matching results learned by the memory network, the visual models on edge devices are further optimized in a self-organized manner. Comprehensive experiments are conducted on several real person Re-ID datasets and deployed on edge devices to show the effectiveness and efficiency of this novel distributed Re-ID model.

Original languageEnglish
Title of host publicationProceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020
EditorsMiltos Alamaniotis, Shimei Pan
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages482-487
Number of pages6
ISBN (Electronic)9781728192284
DOIs
Publication statusPublished - 2020
Event32nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020 - Virtual, Baltimore, United States
Duration: 9 Nov 202011 Nov 2020

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Volume2020-November
ISSN (Print)1082-3409

Conference

Conference32nd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020
CountryUnited States
CityVirtual, Baltimore
Period9/11/2011/11/20

Keywords

  • Distributed
  • Person Re-Identificatlon
  • Self-optimizing
  • Unsupervised

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