Prof. Ing. Adam Herout, Ph.D.

ZAPLETAL Dominik and HEROUT Adam. Vehicle Re-Identification for Automatic Video Traffic Surveillance. In: International Workshop on Automatic Traffic Surveillance (CVPR 2016). Las Vegas: IEEE Computer Society, 2016, pp. 1568-1574. ISBN 978-0-7695-4989-7.
Publication language:english
Original title:Vehicle Re-Identification for Automatic Video Traffic Surveillance
Title (cs):Reidentifikace vozidel pro automatické monitorování dopravy
Proceedings:International Workshop on Automatic Traffic Surveillance (CVPR 2016)
Conference:Computer Vision and Pattern Recognition 2016
Place:Las Vegas, US
Publisher:IEEE Computer Society
vehicle re-identification, traffic monitoring, automatic traffic surveillance
This paper proposes an approach to the vehicle re-identification problem in a multiple camera system.  We focused on the re-identification itself assuming that the vehicle detection problem is already solved including extraction of a full-fledged 3D bounding box. The re-identification problem is solved by using color histograms and histograms of oriented gradients by a linear regressor.  The features are used in separate models in order to get the best results in the shortest CPU computation time. The proposed method works with a high accuracy (60% true positives retrieved with 10% false positive rate on a challenging subset of the test data) in 85 milliseconds of the CPU (Core i7) computation time per one vehicle re-identification assuming the fullHD resolution video input. The applications of this work include finding important parameters such as travel time, traffic flow, or traffic information in a distributed traffic surveillance and monitoring system.
   author = {Dominik Zapletal and Adam Herout},
   title = {Vehicle Re-Identification for Automatic Video
	Traffic Surveillance},
   pages = {1568--1574},
   booktitle = {International Workshop on Automatic Traffic Surveillance
	(CVPR 2016)},
   year = 2016,
   location = {Las Vegas, US},
   publisher = {IEEE Computer Society},
   ISBN = {978-0-7695-4989-7},
   doi = {10.1109/CVPRW.2016.195},
   language = {english},
   url = {}

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