On-Vehicle Videos Localization Using Geometric and Spatio-Temporal Information

Recently, a number of researches are conducted to construct the actual city into computers for the purpose of web services, intelligent transportation systems (ITS), disaster analysis, landscape simulations and so on. Further, with the spread of on-vehicle video cameras, it becomes common to share the on-vehicle video on website. If locations of the videos are available, the data can be efficiently used for virtual city construction. In this paper, the authors propose a method to realize localization of anonymous on-vehicle videos uploaded on the web by using video matching technique with Temporal Height Image (THI), Affine SIFT and Bag of Feature (BoF). THI retains information of relative building heights from temporal image sequences and the Affine SIFT realizes a robust matching for variance of both camera speed and driving lane. Finally, BoF representation allows the authors to realize a stable matching with less computational cost. The authors conducted several experiments using real image sequences of the actual city to show the successful results of the proposed method.

• Availability:
  • Find a library where document is available. Order URL: http://www.its-jp.org/english/congress_e/
• Supplemental Notes:
  • Abstract used with permission of ITS Japan. Paper No. 4140.
• Corporate Authors:

  ITS Japan

  Tokyo,   Japan 
• Authors:
  • Fukumoto, Kazuma
  • Kawasaki, Hiroshi
  • Ono, Shintaro
  • Koyasu, Hiroshi
  • Ikeuchi, Katsushi
• Conference:
  • 20th ITS World Congress
  • Location: Tokyo , Japan
  • Date: 2013-10-14 to 2013-10-18
• Publication Date: 2013

Language

• English

Media Info

• Media Type: Digital/other
• Features: CD-ROM; Figures; Photos; References;
• Pagination: 10p
• Monograph Title: 20th ITS World Congress, Tokyo 2013. Proceedings

Subject/Index Terms

• TRT Terms: Automatic vehicle location; Automotive computers; Disaster preparedness; Intelligent transportation systems; Simulation; Technological innovations; Video cameras; Virtual reality
• Uncontrolled Terms: Localization; Spatiotemporal analysis
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01536384
• Record Type: Publication
• ISBN: 9784990493981
• Files: TRIS
• Created Date: Aug 28 2014 9:12AM