short-paper

Continuous Vehicle Detection and Tracking for Non-overlapping Multi-camera Surveillance System

Authors:

Xianping FuAuthors Info & Claims

ICIMCS'16: Proceedings of the International Conference on Internet Multimedia Computing and Service

Pages 122 - 125

https://doi.org/10.1145/3007669.3007705

Published: 19 August 2016 Publication History

Abstract

Vehicle detection and tracking has always been a significant research on traffic surveillance video. However, multi-camera object tracking consists of a non-overlapping video surveillance network, which makes vehicle re-identification a challenging problem. In this paper, we proposed a novel method for continuous vehicle detection and tracking in multi-camera campus surveillance videos. The method contains two main parts: One is auto vehicle detection and tracking by using background modeling combining with RCNN (Region Convolutional Neural Networks). The other one is multi-camera vehicle re-identification, which collaborates vehicle visual attributes and spatio-temporal information. The experiment results demonstrate that the proposed approach performs with high efficiency and accuracy, which can also be employed to optimize the trajectories of vehicles in multi-camera surveillance videos.

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Cited By

Shan KPenlington MGunner SKoufos KDianati MFairgrieve AKirwan I(2024)Experimental Study of Multi-Camera Infrastructure Perception for V2X-Assisted Automated Driving in Highway MergingIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.342467325:11(16207-16220)Online publication date: Nov-2024
https://doi.org/10.1109/TITS.2024.3424673
Heo JKwon Y(2021)3D Vehicle Trajectory Extraction Using DCNN in an Overlapping Multi-Camera Crossroad SceneSensors10.3390/s2123787921:23(7879)Online publication date: 26-Nov-2021
https://doi.org/10.3390/s21237879
Sabeti SShoghli OBaharani MTabkhi H(2021)Toward AI-enabled augmented reality to enhance the safety of highway work zones: Feasibility, requirements, and challengesAdvanced Engineering Informatics10.1016/j.aei.2021.10142950(101429)Online publication date: Oct-2021
https://doi.org/10.1016/j.aei.2021.101429
Show More Cited By

Index Terms

Continuous Vehicle Detection and Tracking for Non-overlapping Multi-camera Surveillance System
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
        Scene understanding

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cover image ACM Other conferences

ICIMCS'16: Proceedings of the International Conference on Internet Multimedia Computing and Service

August 2016

360 pages

ISBN:9781450348508

DOI:10.1145/3007669

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Xidian University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 August 2016

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Short-paper
Research
Refereed limited

Funding Sources

Fundamental Research of Ministry of Transport of P.R. China
Fundamental Research Funds for the Central Universities
National Natural Science Foundation of China

Conference

ICIMCS'16

ICIMCS'16: International Conference on Internet Multimedia Computing and Service

August 19 - 21, 2016

Xi'an, China

Acceptance Rates

ICIMCS'16 Paper Acceptance Rate 77 of 118 submissions, 65%;

Overall Acceptance Rate 163 of 456 submissions, 36%

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Cited By

Shan KPenlington MGunner SKoufos KDianati MFairgrieve AKirwan I(2024)Experimental Study of Multi-Camera Infrastructure Perception for V2X-Assisted Automated Driving in Highway MergingIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.342467325:11(16207-16220)Online publication date: Nov-2024
https://doi.org/10.1109/TITS.2024.3424673
Heo JKwon Y(2021)3D Vehicle Trajectory Extraction Using DCNN in an Overlapping Multi-Camera Crossroad SceneSensors10.3390/s2123787921:23(7879)Online publication date: 26-Nov-2021
https://doi.org/10.3390/s21237879
Sabeti SShoghli OBaharani MTabkhi H(2021)Toward AI-enabled augmented reality to enhance the safety of highway work zones: Feasibility, requirements, and challengesAdvanced Engineering Informatics10.1016/j.aei.2021.10142950(101429)Online publication date: Oct-2021
https://doi.org/10.1016/j.aei.2021.101429
Hashemi SEmami HBabazadeh Sangar A(2021)A new comparison framework to survey neural networks‐based vehicle detection and classification approachesInternational Journal of Communication Systems10.1002/dac.492834:14Online publication date: 27-Jul-2021
https://doi.org/10.1002/dac.4928
Tang XSong HWang WYang Y(2020)Vehicle Spatial Distribution and 3D Trajectory Extraction Algorithm in a Cross-Camera Traffic SceneSensors10.3390/s2022651720:22(6517)Online publication date: 14-Nov-2020
https://doi.org/10.3390/s20226517

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