relation: https://khub.utp.edu.my/scholars/17241/
title: Investigating the Impact of Illumination and Viewpoint Variations on Transformer-based Person Re-Identification
creator: Amosa, T.I.
creator: Sebastian, P.
creator: Izhar, L.I.
creator: Ibrahim, O.
description: Variations in visual factors such as illumination, viewpoint, resolution, background, pose, and so on are commonly regarded as significant issues in object re-identification (re-ID). Despite widespread recognition of their importance in determining the performance of an object re-ID model, not enough attention is paid to how these factors affect re-ID systems. One of the major impediments to investigating how these factors affect the performance of re-ID models is the lack of datasets with unbiased distribution of these difficult visual conditions. To make up for the lack of large-scale datasets with a balanced distribution of such photometric and geometric transforms, recent studies suggest using game engines to generate synthetic datasets. This study proposes a quantitative investigation of the impact of two critical visual factors: illumination and Tranfomer-based re-ID models on synthetic dataset. © 2022 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2022
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Amosa, T.I. and Sebastian, P. and Izhar, L.I. and Ibrahim, O.  (2022) Investigating the Impact of Illumination and Viewpoint Variations on Transformer-based Person Re-Identification.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149140015&doi=10.1109%2fICFTSC57269.2022.10039913&partnerID=40&md5=a65fb98c4e4c2ba333002ad6cf710834
relation: 10.1109/ICFTSC57269.2022.10039913
identifier: 10.1109/ICFTSC57269.2022.10039913