Learning Feature Aggregation in Temporal Domain for Re-Identification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU134966" target="_blank" >RIV/00216305:26230/19:PU134966 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S107731421830393X" target="_blank" >https://www.sciencedirect.com/science/article/pii/S107731421830393X</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.cviu.2019.102883" target="_blank" >10.1016/j.cviu.2019.102883</a>
Alternative languages
Result language
angličtina
Original language name
Learning Feature Aggregation in Temporal Domain for Re-Identification
Original language description
Person re-identification is a standard and established problem in the computer vision community. In recent years, vehicle re-identification is also getting more attention. In this paper, we focus on both these tasks and propose a method for aggregation of features in temporal domain as it is common to have multiple observations of the same object. The aggregation is based on weighting different elements of the feature vectors by different weights and it is trained in an end-to-end manner by a Siamese network. The experimental results show that our method outperforms other existing methods for feature aggregation in temporal domain on both vehicle and person re-identification tasks. Furthermore, to push research in vehicle re-identification further, we introduce a novel dataset CarsReId74k. The dataset is not limited to frontal/rear viewpoints. It contains 17,681 unique vehicles, 73,976 observed tracks, and 277,236 positive pairs. The dataset was captured by 66 cameras from various angles.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
COMPUTER VISION AND IMAGE UNDERSTANDING
ISSN
1077-3142
e-ISSN
1090-235X
Volume of the periodical
192
Issue of the periodical within the volume
11
Country of publishing house
US - UNITED STATES
Number of pages
12
Pages from-to
1-12
UT code for WoS article
000514226900003
EID of the result in the Scopus database
2-s2.0-85077022950