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Pose estimation for vehicles based on binocular stereo vision in urban traffic

  • Pengyu Liu
  • , Fei Wang
  • , Yicong He
  • , Hang Dong
  • , Haiwei Yang
  • , Yang Yang
  • Xi'an Jiaotong University

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

3 Scopus citations

Abstract

Extensive research has been carried out in the field of driver assistance systems in order to increase road safety and comfort. We propose a pose estimation algorithm based on binocular stereo vision for calculating the pose of on-road vehicles and providing reference for the decision of driving assistant system, which is useful for behavior prediction for vehicles and collision avoidance. Our algorithm is divided into three major stages. In the first part, the vehicle is detected and roughly located on the disparity map. In the second part, feature points on the vehicle are extracted by means of license plate detection algorithm. Finally, pose information including distance, direction and its variation is estimated. Experimental results prove the feasibility of the algorithm in complex traffic scenarios.

Original languageEnglish
Title of host publicationIntelligent Computing Theories and Methodologies - 11th International Conference, ICIC 2015, Proceedings
EditorsVitoantonio Bevilacqua, De-Shuang Huang, Prashan Premaratne
PublisherSpringer Verlag
Pages454-465
Number of pages12
ISBN (Print)9783319221793
DOIs
StatePublished - 2015
Event11th International Conference on Intelligent Computing, ICIC 2015 - Fuzhou, China
Duration: 20 Aug 201523 Aug 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9225
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Intelligent Computing, ICIC 2015
Country/TerritoryChina
CityFuzhou
Period20/08/1523/08/15

Keywords

  • Behavior prediction
  • Binocular stereo vision
  • Pose estimation

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