Publication detail

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

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

Original Title

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

Type

conference paper

Language

English

Original Abstract

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.

Keywords

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

Authors

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

Released

3. 7. 2019

Publisher

IEEE Computer Society

Location

Long Beach

ISBN

2160-7516

Year of study

2019

Number

1

Pages from

150

Pages to

158

Pages count

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",
  volume="2019",
  number="1",
  pages="150--158",
  publisher="IEEE Computer Society",
  address="Long Beach",
  issn="2160-7516",
  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"
}