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A novel route restoring method upon geo-tagged photos

  • Wang, Guannan (School of Mathematics and Statistics, Central South University) ;
  • Wang, Zhizhong (School of Mathematics and Statistics, Central South University) ;
  • Zhu, Zhenmin (Pervasive Computing, Institute of Computing Technology, ChineseAcademy of Sciences, Beijing Key Laboratory of Mobile Computing and Pervasive Device) ;
  • Wen, Saiping (Pervasive Computing, Institute of Computing Technology, ChineseAcademy of Sciences, Beijing Key Laboratory of Mobile Computing and Pervasive Device)
  • Received : 2012.08.13
  • Accepted : 2013.05.09
  • Published : 2013.05.30

Abstract

Sharing geo-tagged photos has been a hot social activity in the daily life because these photos not only contain geo information but also indicate people's hobbies, intention and mobility patterns. However, the present raw geo-tagged photo routes cannot provide information as enough as complete GPS trajectories due to the defects hidden in them. This paper mainly aims at analyzing the large amounts of geo-tagged photos and proposing a novel travel route restoring method. In our approach we first propose an Interest Measure Ratio to rank the hot spots based on density-based spatial clustering arithmetic. Then we apply the Hidden Semi-Markov model and Mean Value method to demonstrate migration discipline in the hot spots and restore the significant region sequence into complete GPS trajectory. At the end of the paper, a novel experiment method is designed to demonstrate that the approach is feasible in restoring route, and there is a good performance.

Keywords

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