Detail publikačního výsledku

Vehicle Re-Identification and Multi-Camera Tracking in Challenging City-Scale Environment

ŠPAŇHEL, J.; BARTL, V.; JURÁNEK, R.; HEROUT, A.

Originální název

Vehicle Re-Identification and Multi-Camera Tracking in Challenging City-Scale Environment

Anglický název

Vehicle Re-Identification and Multi-Camera Tracking in Challenging City-Scale Environment

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

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.

Anglický abstrakt

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.

Klíčová slova

vehicle re-identification, vehicle multi-camera tracking, city-scale environment, camera calibration, neural networks, nvidia ai city challenge

Klíčová slova v angličtině

vehicle re-identification, vehicle multi-camera tracking, city-scale environment, camera calibration, neural networks, nvidia ai city challenge

Autoři

ŠPAŇHEL, J.; BARTL, V.; JURÁNEK, R.; HEROUT, A.

Rok RIV

2020

Vydáno

03.07.2019

Nakladatel

IEEE Computer Society

Místo

Long Beach

Kniha

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Edice

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

ISSN

2160-7516

Periodikum

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Svazek

2019

Číslo

1

Stát

Spojené státy americké

Strany od

150

Strany do

158

Strany počet

9

URL

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

BibTex

@inproceedings{BUT162081,
  author="Jakub {Špaňhel} and Vojtěch {Bartl} and Roman {Juránek} and Adam {Herout}",
  title="Vehicle Re-Identification and Multi-Camera Tracking in Challenging City-Scale Environment",
  booktitle="2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
  year="2019",
  series="IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops",
  journal="IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops",
  volume="2019",
  number="1",
  pages="150--158",
  publisher="IEEE Computer Society",
  address="Long Beach",
  issn="2160-7508",
  url="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"
}