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2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) (2017)
Lecce, Italy
Aug. 29, 2017 to Sept. 1, 2017
ISBN: 978-1-5386-2940-6
pp: 1-7
Siwei Lyu , University at Albany, State University of New York, USA
Ming-Ching Chang , University at Albany, State University of New York, USA
Dawei Du , University of Chinese Academy of Sciences, China
Longyin Wen , GE Global Research, USA
Honggang Qi , University of Chinese Academy of Sciences, China
Yuezun Li , University at Albany, State University of New York, USA
Yi Wei , University at Albany, State University of New York, USA
Lipeng Ke , University of Chinese Academy of Sciences, China
Tao Hu , University of Chinese Academy of Sciences, China
Marco Del Coco , National Research Council, Italy
Pierluigi Carcagni , National Research Council, Italy
Dmitriy Anisimov , Intel, Nizhny Novgorod, Russia
Erik Bochinski , Technische Universität Berlin, Germany
Fabio Galasso , OSRAM GmbH, Germany
Filiz Bunyak , University of Missouri Columbia, USA
Guang Han , Nanjing University of Posts and Telecommunications, China
Hao Ye , Shanghai Advanced Research Institute, Chinese Academy of Sciences, China
Hong Wang , Shanghai Advanced Research Institute, Chinese Academy of Sciences, China
Kannappan Palaniappan , University of Missouri Columbia, USA
Koray Ozcan , Iowa State University, USA
Li Wang , Fudan University, China
Liang Wang , Institute of Automation, Chinese Academy of Sciences, China
Martin Lauer , Karlsruhe Institute of Technology, Germany
Nattachai Watcharapinchai , National Electronics and Computer Technology Center, Thailand
Nenghui Song , University at Albany, State University of New York, USA
Noor M. Al-Shakarji , University of Missouri Columbia, USA
Shuo Wang , Iowa State University, USA
Sikandar Amin , OSRAM GmbH, Germany
Sitapa Rujikietgumjorn , National Electronics and Computer Technology Center, Thailand
Tatiana Khanova , Intel, Nizhny Novgorod, Russia
Thomas Sikora , Technische Universität Berlin, Germany
Tino Kutschbach , Technische Universität Berlin, Germany
Volker Eiselein , Technische Universität Berlin, Germany
Wei Tian , Karlsruhe Institute of Technology, Germany
Xiangyang Xue , Fudan University, China
Xiaoyi Yu , Nanjing University of Posts and Telecommunications, China
Yao Lu , University of Washington, USA
Yingbin Zheng , Shanghai Advanced Research Institute, Chinese Academy of Sciences, China
Yongzhen Huang , Institute of Automation, Chinese Academy of Sciences, China
Yuqi Zhang , Institute of Automation, Chinese Academy of Sciences, China
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.
INDEX TERMS
Benchmark testing, Surveillance, Measurement, Detectors, Protocols
CITATION

S. Lyu et al., "UA-DETRAC 2017: Report of AVSS2017 & IWT4S Challenge on Advanced Traffic Monitoring," 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Lecce, Italy, 2017, pp. 1-7.
doi:10.1109/AVSS.2017.8078560
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