ZHANG Xing, LI Qingquan, FANG Zhixiang. An Approach of Generating Landmark Chain for Pedestrian Navigation Applications[J]. Geomatics and Information Science of Wuhan University, 2010, 35(10): 1240-1244.
Citation: ZHANG Xing, LI Qingquan, FANG Zhixiang. An Approach of Generating Landmark Chain for Pedestrian Navigation Applications[J]. Geomatics and Information Science of Wuhan University, 2010, 35(10): 1240-1244.

An Approach of Generating Landmark Chain for Pedestrian Navigation Applications

Funds: 国家自然科学基金资助项目(40701153,60872132,40830530);国家教育部博士点专项基金资助项目(20070486001)
More Information
  • Received Date: July 08, 2013
  • Revised Date: July 08, 2013
  • Published Date: October 04, 2010
  • Landmarks are predominant spatial features and play an important role in pedestrian navigation.This paper proposes a novel approach,landmark Chain,to include landmark information in pedestrian navigation applications.This approach is able to generate image sequences of landmarks for route guidance based on oriented visibility graph.An algorithm used for oriented visibility graph construction and landmark Chain generation is described.Results show that the proposed approach is able to provide guidance information by using image sequences with limited number of landmark images.
  • Related Articles

    [1]JIANG Zhenxiang, CHEN Hui, CHEN Luwan. A Multi‑model Early Warning Method for Dam Displacement Behavior[J]. Geomatics and Information Science of Wuhan University, 2024, 49(2): 280-290. DOI: 10.13203/j.whugis20210321
    [2]LI Guangchun, DAI Wujiao, YANG Guoxiang, LIU Bin. Application of Space-Time Auto-Regressive Model in Dam Deformation Analysis[J]. Geomatics and Information Science of Wuhan University, 2015, 40(7): 877-893. DOI: 10.13203/j.whugis20130549
    [3]Lu Jun, Dai Wujiao, Zhang Zhetao. Modeling Dam Deformation Using Varying Coefficient Regression[J]. Geomatics and Information Science of Wuhan University, 2015, 40(1): 139-142.
    [4]ZHAO Qing, HUANG Shengxiang. A Way for Overall Analysis on Dam's Displacement[J]. Geomatics and Information Science of Wuhan University, 2009, 34(12): 1419-1422.
    [5]WANG Xinzhou, FAN Qian, XU Chengquan, LI Zhao. Dam Deformation Prediction Based on Wavelet Transform and Support Vector Machine[J]. Geomatics and Information Science of Wuhan University, 2008, 33(5): 469-471.
    [6]WANG Xinzhou DENG Xingsheng, . Fuzzy Neural Network Modeling for Dam Deformation Prediction[J]. Geomatics and Information Science of Wuhan University, 2005, 30(7): 588-591.
    [7]ZHANG Chaoyu. Multi-dimensional AR Series Modeled by Least Square Criterion[J]. Geomatics and Information Science of Wuhan University, 2002, 27(4): 377-381.
    [8]Deng Yuejin, Dong Zhaowei, Zhang Zhenglu. A Cusp Catastrophe Model of Large Dam Deformation Destabilization[J]. Geomatics and Information Science of Wuhan University, 1999, 24(2): 170-173.
    [9]Lan Yueming, Wang Xinzhou. Research of Grey Forecast on Dam Level Displacement[J]. Geomatics and Information Science of Wuhan University, 1996, 21(4): 350-354.
    [10]Wu Zian. The Independent Variablas-snooping in the Regression Analysis of Dam Deformation[J]. Geomatics and Information Science of Wuhan University, 1993, 18(1): 20-26.

Catalog

    Article views (1362) PDF downloads (475) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return