Attention in Multimodal Neural Networks for Person Re-identification

Aske Rasch Lejbølle, Benjamin Krogh, Kamal Nasrollahi, Thomas B. Moeslund

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

6 Citations (Scopus)
334 Downloads (Pure)

Abstract

In spite of increasing interest from the research commu-
nity, person re-identification remains an unsolved problem.
Correctly deciding on a true match by comparing images
of a person, captured by several cameras, requires extrac-
tion of discriminative features to counter challenges such as
changes in lighting, viewpoint and occlusion. Besides de-
vising novel feature descriptors, the setup can be changed
to capture persons from an overhead viewpoint rather than
a horizontal. Furthermore, additional modalities can be
considered that are not affected by similar environmental
changes as RGB images. In this work, we present a Multi-
modal ATtention network (MAT) based on RGB and depth
modalities. We combine a Convolution Neural Network with
an attention module to extract local and discriminative fea-
tures that are fused with globally extracted features. At-
tention is based on correlation between the two modalities
and we finally also fuse RGB and depth features to generate
a joint multilevel RGB-D feature. Experiments conducted
on three datasets captured from an overhead view show the
importance of attention, increasing accuracies by 3.43%,
2.01% and 2.13% on OPR, DPI-T and TVPR, respectively.
Original languageEnglish
Title of host publication2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Number of pages9
PublisherIEEE
Publication dateJun 2018
Pages292-300
ISBN (Print)978-1-5386-6101-7
ISBN (Electronic)978-1-5386-6100-0
DOIs
Publication statusPublished - Jun 2018
EventIEEE Conference on Computer Vision and Pattern Recognition, 2018 - Salt Lake City, United States
Duration: 18 Jun 201822 Jun 2018

Conference

ConferenceIEEE Conference on Computer Vision and Pattern Recognition, 2018
CountryUnited States
CitySalt Lake City
Period18/06/201822/06/2018
SeriesIEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
ISSN2160-7516

Fingerprint Dive into the research topics of 'Attention in Multimodal Neural Networks for Person Re-identification'. Together they form a unique fingerprint.

Cite this