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研究生： 林宜姮
Yi-Hegn Lin
論文名稱： Inferring Floor Plan from Trajectories
指導教授： 孫敏德
Min-Te Sun
口試委員:
學位類別： 碩士
Master
系所名稱： 資訊電機學院 - 資訊工程學系
Department of Computer Science & Information Engineering
論文出版年： 2013
畢業學年度： 101
語文別： 英文
論文頁數： 30
中文關鍵詞： 室內定位
相關次數： 點閱：9  下載：0 
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    • 近年來，行動定位服務漸漸由室外轉向室內，因此須要室內地圖配合以提供完整服務。然而，取得室內地圖有一定的困難，有些建築物過於老舊以至於平面圖並未保留；有些建築物的所有者可能不願意提供平面圖：若要手動為每一棟建築物建置平面圖，所耗費的人力及費用勢必相當可觀。因此，本篇論文提出一套利用收集的行人軌跡資料建置室內平面圖的方法(Traces-to-Map, T2M)。首先，T2M分析行人軌跡的分佈，建立樓層中牆壁的部分，接著再分析軌跡特性，判斷某個區域為房間或走廊。透過在不同平面圖上的實驗證實，T2M建置出的平面圖很接近實際的平面圖。

    Indoor localization has significant growth in recent years. The key requirement to indoor location based-service (LBS) is the availability of floor plans. However, floor plans may be difficult to obtain.
    In this thesis, we present a system, Traces-to-Map (T2M), that automatically infers floor plans from pedestrian trajectories collected by smartphones. T2M consists of two parts.
    First, it takes advantage of collected trajectories to infer a floor plan with wall information.
    Second, it identifies the region type by considering the standard deviation of moving directions within an area. We validate our method with multiple floor plans. The result shows the T2M system is able to provide a floor plan highly correlated to the real floor plan.

    Contents 1 Introduction 1 2 Literature Review 2 3 Traces-to-Map System 4 3.1 Wall Construction 5 3.1.1 Inferring Walls and Identifying Missing Parts 5 3.1.2 Removing Isolated Wall Parts 6 3.2 Room-Corridor Identification 7 3.2.1 Identifying the Region Type 7 4 Evaluation 9 4.1 Testbeds 9 4.2 Process of T2M 10 4.2.1 Wall Construction 10 4.2.2 Room-Corridor Identification 12 4.3 Floor Plan Construction Accuracy 13 4.3.1 Number of Room 14 4.3.2 Wall-Room/Corridor Inference Accuracy 15 4.3.3 Graph and Shape Discrepancy Metric 16 5 Conclusion 20 Reference 21

    [1] “Google Maps,” http://maps.google.com/help/maps/indoormaps/index.html.
    [2] “IndoorAtlas,” http://www.indooratlas.com.
    [3] “WifiSlam,” https://angel.co/wifislam.
    [4] “WiFi Alliance,” http://www.wi-fi.org/.
    [5] C.-C. Wang, C. E. Thorpe, S. Thrun, M. Hebert, and H. F. Durrant-Whyte, “Simultaneous localization, mapping and
    moving object tracking,” I. J. Robotic Res., vol. 26, no. 9, pp. 889–916, 2007.
    [6] H. Shin, Y. Chon, and H. Cha, “Unsupervised construction of an indoor floor plan using a smartphone,” IEEE
    Transactions on Systems, Man, and Cybernetics, Part C, vol. 42, no. 6, pp. 889–898, 2012.
    [7] G. Shen, Z. Chen, P. Zhang, T. Moscibroda, and Y. Zhang, “Walkie-markie: indoor pathway mapping made easy,” in
    Proceedings of the 10th USENIX conference on Networked Systems Design and Implementation, 2013, pp. 85–98.
    [8] W. Chang, J.Wu, and C. C. Tan, “Cooperative trajectory-based map construction,” in Proceedings of IEEE TrustCom,
    2012, pp. 497–504.
    [9] M. Alzantot and M. Youssef, “Crowdinside: automatic construction of indoor floorplans,” in Proceedings of ACM
    SIGSPATIAL GIS, 2012, pp. 99–108.
    [10] J.-G. Lee, J. Han, X. Li, and H. Gonzalez, “TraClass: trajectory classification using hierarchical region-based and
    trajectory-based clustering,” PVLDB, vol. 1, no. 1, pp. 1081–1094, 2008.

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