Vehicle Motion Segmentation using Rigid Motion Constraints in Traffic Video

Vehicle motion segmentation is an important task in intelligent transportation systems (ITS) for the sustainable development of smart city. In this paper, a novel trajectory clustering method is proposed using the rigid motion constraints (RMC) for the vehicle motion segmentation. Firstly, camera calibration is done for converting the 2D images to a copy one in 3D world. Then, the inverse projection image (IPI) can be obtained with a known 3D height information and the 2D image. Secondly, the authors present and verify the RMC of the feature point trajectories in the same rigid object and different rigid objects. By analyzing simulation results, the authors use the RMC as a measure to define the similarity function. Finally, spectral clustering is adopted to achieve the trajectory clustering, which contains two stages: initial clustering and inter-class merging. By applying this clustering method in actual traffic scene, much more stable clustering results can be obtained. Experimental results on traffic video demonstrate that the proposed method has a good performance in different traffic scenes. Moreover, its accuracy can reach 96% compared with other methods.

• Record URL:
  • https://doi.org/10.1016/j.scs.2018.07.026
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2210670717310089
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/22106707
• Supplemental Notes:
  • © 2018 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Wang, Xuan
  • Song, Huansheng
  • Guan, Qi
  • Cui, Hua
  • Zhang, Zhaoyang
  • Liu, Haiying
• Publication Date: 2018-10

Language

• English

Media Info

• Media Type: Web
• Features: Figures; Photos; References; Tables;
• Pagination: pp 547-557
• Serial:
  • Sustainable Cities and Society
  • Volume: 42
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2210-6707
  • Serial URL: http://www.sciencedirect.com/science/journal/22106707?sdc=2

Subject/Index Terms

• TRT Terms: Data segmentation; Image processing; Motion; Traffic surveillance
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01680787
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 18 2018 9:36AM