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UA-DETRAC 2017: Report of AVSS2017 & IWT4S Challenge on Advanced Traffic Monitoring

  • Siwei Lyu
  • , Ming Ching Chang
  • , Dawei Du
  • , Longyin Wen
  • , Honggang Qi
  • , Yuezun Li
  • , Yi Wei
  • , Lipeng Ke
  • , Tao Hu
  • , Marco Del Coco
  • , Pierluigi Carcagni
  • , Dmitriy Anisimov
  • , Erik Bochinski
  • , Fabio Galasso
  • , Filiz Bunyak
  • , Guang Han
  • , Hao Ye
  • , Hong Wang
  • , Kannappan Palaniappan
  • , Koray Ozcan
  • Li Wang, Liang Wang, Martin Lauer, Nattachai Watcharapinchai, Nenghui Song, Noor M. Al-Shakarji, Shuo Wang, Sikandar Amin, Sitapa Rujikietgumjorn, Tatiana Khanova, Thomas Sikora, Tino Kutschbach, Volker Eiselein, Wei Tian, Xiangyang Xue, Xiaoyi Yu, Yao Lu, Yingbin Zheng, Yongzhen Huang, Yuqi Zhang
  • SUNY Albany
  • University of Chinese Academy of Sciences
  • General Electric
  • National Research Council of Italy
  • Intel
  • Technical University of Berlin
  • OSRAM Licht AG
  • University of Missouri
  • Nanjing University of Posts and Telecommunications
  • CAS - Shanghai Advanced Research Institute
  • Iowa State University
  • Fudan University
  • Chinese Academy of Sciences
  • Karlsruhe Institute of Technology
  • National Science and Technology Development Agency Thailand
  • University of Washington

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

82 Scopus citations

Abstract

The rapid advances of transportation infrastructure have led to a dramatic increase in the demand for smart systems capable of monitoring traffic and street safety. Fundamental to these applications are a community-based evaluation platform and benchmark for object detection and multi-object tracking. To this end, we organize the AVSS2017 Challenge on Advanced Traffic Monitoring, in conjunction with the International Workshop on Traffic and Street Surveillance for Safety and Security (IWT4S), to evaluate the state-of-the-art object detection and multi-object tracking algorithms in the relevance of traffic surveillance. Submitted algorithms are evaluated using the large-scale UA-DETRAC benchmark and evaluation protocol. The benchmark, the evaluation toolkit and the algorithm performance are publicly available from the website http://detrac-db.rit.albany.edu.

Original languageEnglish
Title of host publication2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538629390
DOIs
StatePublished - Oct 20 2017
Event14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017 - Lecce, Italy
Duration: Aug 29 2017Sep 1 2017

Publication series

Name2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017

Conference

Conference14th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2017
Country/TerritoryItaly
CityLecce
Period08/29/1709/1/17

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