Investigating Open-World Person Re-identification Using a Drone

Ryan Layne, Timothy M. Hospedales, Shaogang Gong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Person re-identification is now one of the most topical and intensively studied problems in computer vision due to its challenging nature and its critical role in underpinning many multi-camera surveillance tasks. A fundamental assumption in almost all existing re-identification research is that cameras are in fixed emplacements, allowing the explicit modelling of camera and inter-camera properties in order to improve re-identification. In this paper, we present an introductory study pushing re-identification in a different direction: re-identification on a mobile platform, such as a drone. We formalise some variants of the standard formulation for re-identification that are more relevant for mobile re-identification. We introduce the first dataset for mobile re-identification, and we use this to elucidate the unique challenges of mobile re-identification. Finally, we re-evaluate some conventional wisdom about re-id models in the light of these challenges and suggest future avenues for research in this area.
Original languageEnglish
Title of host publicationComputer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part III
PublisherSpringer International Publishing
Pages225-240
Number of pages16
ISBN (Electronic)978-3-319-16199-0
ISBN (Print)978-3-319-16198-3
DOIs
Publication statusPublished - 2014

Publication series

NameLecture Notes in Computer Science (LNCS)
PublisherSpringer International Publishing
Volume8927
ISSN (Print)0302-9743

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