Lane detection in surveillance videos using vector-based hierarchy clustering and density verification

Shan Yun Teng, Kun Ta Chuang, Chun Rong Huang, Cheng Chun Li

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

Automatic lane detection is known to facilitate the real-time traffic planning and identify traffic congestion. In this paper, we develop a visual surveillance trajectory clustering (VSTC) framework for automatic lane detection. Given a surveillance video, trajectories of vehicles are extracted at first. These trajectories contain behavior of vehicles on different lanes and are clustered by VSTC to retrieve candidate lanes. Finally, a density verification is applied to identify the correct lanes from candidate lanes. As shown in the experiments, our framework can identify the lanes by using trajectories without prior knowledge.

原文English
主出版物標題Proceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015
發行者Institute of Electrical and Electronics Engineers Inc.
頁面345-348
頁數4
ISBN(電子)9784901122153
DOIs
出版狀態Published - 2015 七月 8
事件14th IAPR International Conference on Machine Vision Applications, MVA 2015 - Tokyo, Japan
持續時間: 2015 五月 182015 五月 22

出版系列

名字Proceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015

Other

Other14th IAPR International Conference on Machine Vision Applications, MVA 2015
國家/地區Japan
城市Tokyo
期間15-05-1815-05-22

All Science Journal Classification (ASJC) codes

  • 電腦科學應用
  • 電腦視覺和模式識別

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