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A high accurate vehicle speed estimation method

  • Shengnan LuEmail author
  • Yuping Wang
  • Huansheng Song
Methodologies and Application
  • 26 Downloads

Abstract

In this paper, we present a novel approach for accurate vehicle speed estimation from video sequences. Common methods usually track sets of distinguishing features; however, feature extraction is a difficult task in dynamic environments. Herein, we propose a novel analysis method without feature extraction. Initially, a frame difference method is applied to a region of interest, from which projection histograms are obtained and a group of key bins are selected to represent the vehicle motion. Then, all the possible speeds are tested one by one, and the extreme value of the testing function is selected for the corresponding speed. The proposed system was tested on three data sets containing 2054 vehicles, where the ground truth of speed is obtained by a radar speed detector. The experiment results show that the proposed system has an average error of 0.3 km/h, with 99.4% of the estimation speed within the error of range (− 2 km/h, 2 km/h). The system turns out to be robust, accurate and real time for practical use.

Keywords

Vehicle speed estimation Camera calibration Projection histogram Speed enumeration 

Notes

Funding

This study was funded by National Natural Science Foundation of China (Grant No. 61572083), funded by Scientific Research Program Funded by Shaanxi Provincial Education Department (Program No. 18JK0617). This study was also funded by the Doctoral Scientific Research Foundation of Xi’an Shiyou University (0106-134010003).

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Xi’an shiyou UniversityXi’anChina
  2. 2.Tulane UniversityNew OrleansUS
  3. 3.Chang’an UniversityXi’anChina

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