Vehicle Re-Identification and Multi-Camera Tracking in Challenging City-Scale Environment
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU135361" target="_blank" >RIV/00216305:26230/19:PU135361 - isvavai.cz</a>
Result on the web
<a href="http://openaccess.thecvf.com/content_CVPRW_2019/html/AI_City/Spanhel_Vehicle_Re-Identifiation_and_Multi-Camera_Tracking_in_Challenging_City-Scale_Environment_CVPRW_2019_paper.html" target="_blank" >http://openaccess.thecvf.com/content_CVPRW_2019/html/AI_City/Spanhel_Vehicle_Re-Identifiation_and_Multi-Camera_Tracking_in_Challenging_City-Scale_Environment_CVPRW_2019_paper.html</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Vehicle Re-Identification and Multi-Camera Tracking in Challenging City-Scale Environment
Original language description
In our submission to the NVIDIA AI City Challenge, we address vehicle re-identification and vehicle multi-camera tracking. Our approach to vehicle re-identification is based on the extraction of visual features and aggregation of these features in the temporal domain to obtain a single feature descriptor for the whole observed track. For multi-camera tracking, we proposed a method for matching vehicles by the position of trajectory points in real-world space (linear coordinate system). Furthermore, we use CNN for the vehicle re-identification task to filter out false matches generated by proposed positional matching method for better results.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
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
Article name in the collection
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
ISBN
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ISSN
2160-7516
e-ISSN
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Number of pages
9
Pages from-to
150-158
Publisher name
IEEE Computer Society
Place of publication
Long Beach
Event location
Long Beach, California
Event date
Jun 16, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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