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The cooperative vehicle infrastructure system based on machine vision

  • Beihang University
  • University of Sussex
  • University of British Columbia

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

The information acquisition is a key procedure of cooperative vehicle-infrastructure system (CVIS). With the advancement of computer image processing technology, more and more researchers use image recognition as the source of information acquisition. On this background, the authors develop a CVIS based on machine vision, including vehicular subsystem, the roadside subsystem and the parking lot subsystem. The system uses improved Canny algorithm to detect road channelization, HOG+SVM method to detect pedestrian and Haar+Adaboost method to detect vehicle. The experiment result shows that the detection accuracy and real-time of system is relatively high. In addition, the test also prove that the system is significant in driving assistance.

源语言英语
主期刊名DIVANet 2017 - Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications, Co-located with MSWiM 2017
出版商Association for Computing Machinery, Inc
85-89
页数5
ISBN(电子版)9781450351645
DOI
出版状态已出版 - 21 11月 2017
活动6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications, Co-located with MSWiM 2017 - Miami, 美国
期限: 21 11月 201725 11月 2017

出版系列

姓名DIVANet 2017 - Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications, Co-located with MSWiM 2017

会议

会议6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications, Co-located with MSWiM 2017
国家/地区美国
Miami
时期21/11/1725/11/17

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