旅遊地圖是一種有助於旅遊的地圖，它透過顯眼的圖像或插畫來凸顯重要地標和景點，讓使用者快速掌握當地最有特色，最值得參觀。但是，因為地圖空間有限的關係，為了加入這些插圖，旅遊地圖的細小路段或巷子通常都會被省略，路網的結構也免不了一些扭曲，而使用者很容易因為地圖上的表現方式和實際地段的外觀不同而產生困惑，例如：旅遊地圖所畫的路段長度跟實際長度不同，讓使用者不清楚是否已經經過某個路口，或使用者行走到旅遊地圖上被省略的路段，很容易導致迷路。

為了解決旅遊地圖因為沒有相對實際位置而造成使用者的困擾這個問題，我們開發一個旅遊地圖導航系統。這個系統透過利用道路網絡對應和GPS定位來改善使用旅遊地圖的體驗，讓使用者不僅利用旅遊地圖了解景點的特色，還可以順利到達目的地。 具體的說,本系統計算旅遊地圖和一般地圖之間的道路網絡對應，然後在手機應用程式裡把GPS坐標位置表示在旅遊地圖上。最後，為了評估提出的系統，我們進行調查總共30位男女的使用者經驗，請他們使用我們的系統和另外開發的全手動標記對應系統來找出旅遊和一般地圖的路網對應。結果顯示我們的系統比全手動系統節省力氣和被認為有效的縮短找對應時間。對於我們的系統對觀光的幫助， 所有參與的實驗者都給予積極的反饋。

We present OpenTourMap - a GPS positioning on tourist maps system to enhance tourist wayfinding experience. Our system incorporated two applications, the desktop application runs on PC and the mobile application on Android phone. Specifically, the desktop application computes road network correspondence between tourist maps and general maps and allows users to correct the road network correspondence with full-control ability. Then mobile application provides the user’s current location on the tourist map by plotting their GPS coordinates on the map.
Finally, to examine the effectiveness of the desktop application and the usefulness of mobile application, we carried out a formal user study and report about the feedback obtained from it. The results showed that our desktop application is perceived boosting the mapping process and the mobile application has made a significant improvement to the wayfinding experience of users while exploring unfamiliar areas.

Chinese Abstract i
Abstract ii
Acknowledgments iii
Table of Contents iv
List of Figures vi
Chapter 1: Introduction 1
Chapter 2: Related Work 3
2.1. GPS-based mobile guides 3
2.2. Road Network Matching 3
Chapter 3: System Requirement 4
Chapter 4: Road Matching Desktop Application 8
4.1. OSM window 8
4.2. Phase type program 9
4.3. Road Network Optimization 10
4.3.1. Road Mask Modifying 10
4.3.2. Road Network Structure Modifying 11
4.4. Preserve user’s modification on road network structure 12
4.5. GPS-enabled tourist map sharing platform 13
4.5.1. Map package landing page with sort and search function 14
4.5.2. Download and modify the off-the-shelf map package 14
4.6. System flow 15
Chapter 5: GPS Navigation Mobile Application 19
Chapter 6: System Result 20
Chapter 7: Conclusion 24
References 24

[1] Chih Hsiang Hsu. Robust Road Network Matching for Tourist Map Navigation. Computer Graphics and Visualization Laboratory, Department of Computer Science, National Chiao Tung University, Taiwan
[2] Todd, Stephen, and Bruce H., Developing a Location Based Tourist Guide Application. Workshop on Wearable, Invisible, Context Aware, Ambient, Pervasive and Ubiquitous Computing, Adelaide, Australia
[3] Yoji, and Toshiyuki, Pedestrian Navigation System for Mobile Phones Using Panoramic Landscape Images. Proceedings of the 2005 Symposium on Applications and the Internet (SAINT’06)
[4] Stefano, Luca, Location-aware Visualization of VRML Models in GPS-based Mobile Guides. HCI Lab Dept. of Math and Computer Science University of Udine via delle Scienze
[5] Katri Laakso, Ove G., Jan R. S., Tourist information and navigation support by using 3D maps displayed on mobile devices. Workshop "HCI in mobile Guides", Udine (Italy), 8 September 2003
[6] Maria Andréia F. R., Rafael G. B., and Nabor C. M., Interactive Mobile 3D Graphics for On-the-go Visualization and Walkthroughs. Mestrado em Informática Aplicada Universidade de Fortaleza
[7] E. Safra, Y. Kanza, Y. Sagiv, and Y. Doytsher. Ad hoc matching of vectorial road networks. International Journal of Geographical Information Science, 27(1):114–153, 2013.
[8] A. Samal, S. C. Seth, and K. Cueto. A feature-based approach to conflation of geospatial sources. International Journal of Geographical Information Science, 18(5):459–489, 2004.
[9] S. Musti´ere and T. Devogele. Matching networks with different levels of detail. Geoinformatica, 12(4):435–453, 2008.
[10] Y. Zhang, B. Yang, and X. Luan, “AUTOMATED MATCHING CROWDSOURCING ROAD NETWORKS USING PROBABILISTIC RELAXATION”, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. I-4, pp. 281-286, 2012
[11] J. Zhang, Y. Zhu, and L. Meng, “Conflation of Road Network and Geo-Referenced Image Using Sparse Matching”, GIS ’11, pp. 281-288, 2011
[12] W. Song, J. M. Keller, T. L. Haithcoat, and C. H. Davis, “Automated Geospatial Conflation of Vector Road Maps to High Resolution Imagery”, vol. 18, no. 2, pp. 388-400, 2008
[13] T. Y. Zhang, and C. Y. Suen, “A fast parallel algorithm for thinning digital patterns”, Communications of the ACM, vol. 27, no. 3, pp. 236-239, 1984.