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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陳炳宇(Bing-Yu Chen) | |
dc.contributor.author | Chi Peng | en |
dc.contributor.author | 彭騏 | zh_TW |
dc.date.accessioned | 2021-06-15T05:03:34Z | - |
dc.date.available | 2010-07-30 | |
dc.date.copyright | 2010-07-30 | |
dc.date.issued | 2010 | |
dc.date.submitted | 2010-07-27 | |
dc.identifier.citation | [1] A.A. Efros and W.T. Freeman. Image quilting for texture synthesis and transfer. Proc. Siggraph 2001, pages 341–346, August 2001.
[2] A. Lippman. Movie-maps: An application of the optical videodisc to computer graphics. SIGGRAPH Comput. Graph., 14(3):32–42, 1980. [3] B. Chen, B. Neubert, E. Ofek, O. Deussen, and M. F. Cohen. Integrated Videos and Maps for Driving Directions. User Interface Science and Technology (UIST), 2009. [4] B. Tversky and P. U. Lee. Pictorial and verbal tools for conveying routes. In COSIT ’99: Proceedings of the International Conference on Spatial Information Theory: Cognitive and Computational Foundations of Geographic Information Science, pages 51–64, London, UK, 1999. Springer-Verlag. [5] C. Harris and M. Stephens. A combined corner and edge detector. In Fourth Alvey Vision Conference, Manchester, UK, pp. 147-151, 1988. [6] C. Jones and S. Healy. Differences in cue use and spatial memory in men and women. Proceedings of the Royal Society, 2006. [7] C. Rother, L. Bordeaux, Y. Hamadi, and A. Blake. Autocollage. In Proc. ACM SIGGRAPH, 2006. [8] Coding4Fun: http://blogs.msdn.com/coding4fun/default.aspx [9] D. G. Lowe, Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60, 2 (2004), pp. 91-110. [10] D. G. Lowe. Object recognition from local scale-invariant features. In International Conference on Computer Vision, Corfu, Greece, pp. 1150-1157, 1999. [11] E. Robinson. An Implementation of the Efros and Freeman Image Quilting Algorithm. [12] e-glue: http://code.google.com/p/e-glue/ [13] G. Satalich. Navigation and wayfinding in virtual reality: Finding proper tools and cues to enhance navigation awareness. Master’s thesis, HitLab, University of Washington, Seattle, WA, 1995. [14] H. Moravec. Rover visual obstacle avoidance. In International Joint Conference on Artificial Intelligence, Vancouver, Canada, pp. 785-790, 1981. [15] Glyn W. Humphreys and M. Jane Riddoch. To See But Not to See: A Case Study of Visual Agnosia. Psychology Press Ltd., 1987. [16] Glassner, A. (ed) An Introduction to Ray Tracing. Academic Press New York, N.Y. 1989. [17] J. Kopf, B. Chen, R. Szeliski, and M. Cohen. Street Slide: Browsing Street Level Imagery. SIGGRAPH 2010. [18] J. Kopf, M. Uyttendaele, O. Deussen, and M. Cohen. Capturing and viewing gigapixel images. ACM Transactions on Graphics, 26(3), 2007. [19] J. LONG and D. MOULD. 2007. Improved image quilting. ACM International Conference Proceeding Series; Vol. 234. Proceedings of Graphics Interface 2007, 257- 264. ISBN : 0713-5424. [20] J. Sivic, B. Kaneva, A. Torralba, S. Avidan, and W. T. Freeman. Creating and exploring a large photorealistic virtual space. In First IEEE Workshop on Internet Vision, associated with CVPR, 2008. [21] M. Brown and D. G. Lowe. Recognising Panoramas. In Proceedings of the 9th International Conference on Computer Vision (ICCV2003), pages 1218-1225, Nice, France, 2003. [22] My Google Street View Time Lapse experiment: http://ejtaal.net/streetview/ [23] N. Snavely, S. M. Seitz, and R. Szeliski. Photo tourism: Exploring photo collections in 3d. In Proc. ACM SIGGRAPH, 2006. [24] P. J. Burt and E. H. Adelson. A Multiresolution Spline With Application to Image Mosaics. ACM Transactions on Graphics, Vol. 2, No. 4, pp.217-236, Oct. 1983. [25] P. P | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/46323 | - |
dc.description.abstract | 在使用電子地圖規劃路線時,經常會有只能看到路線走法與道路名稱,而對於實際上依照路線行進時的景色不甚了解,因而不能依規劃的路線正確行進的情況。
在這篇論文中,我們提出一個系統可以接受使用者輸入路線的起點與終點,該系統便會自動連線到Google,並藉由Google Map的路線規劃與Google Street View的景色,輸出從該路線起點到終點的流暢影片。配合Google Map的即時地圖對應,使用者便可以了解在路線中行進到不同位置時的不同景色,也可以如同坐在車上一般順暢的瀏覽整個路線。 這個系統的過程為全自動的,並且憑藉著目前較易取得的Google Street View圖片,配合Image Alignment與Poisson Blending,便可以將路線上每一張圖片串成連續的影片,進而輸出視覺上近似真實的效果。 當結果影片輸出之後,使用者可以讓系統從頭到尾自動播放,也可以自由拖曳影片以決定想看的部分及播放的速度。當需要仔細觀察周遭景色時,也可以將目前所在位置的全景圖另外再開一個視窗,在該視窗中使用者可以用滑鼠控制想要觀察的方向。 | zh_TW |
dc.description.abstract | While planning route with electronic maps, we often only know about driving direction and the name of the streets, but we could not know the scenery along the route. Thus, it is sometimes hard for us to drive through the planned route in reality.
In this thesis, we provide a system that takes start and end point as input, and it will automatically connect to Google Map and Google Street View, downloading route information and scenery along the route. Finally it will generate smooth scenic video from starting point to destination, which combines maps to provide better route recognition. Users can watch the video as if they are driving a car through the planned route. Our system is fully automatic, downloading panoramas from Google Street View and combines each picture with image alignment and blending technique to create a continuous video, with visually real quality. With the output video, user can let the system play the video from start to end, or user can browse the video with slider to choose which part he wants to see and adjusts playing speed. When user feels the need to see the scene around him, he can open up another window with panorama image of current position, and he can view the scene with mouse. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T05:03:34Z (GMT). No. of bitstreams: 1 ntu-99-R97944007-1.pdf: 3096886 bytes, checksum: 60169092131e49102effbbb197898a9e (MD5) Previous issue date: 2010 | en |
dc.description.tableofcontents | Contents
摘 要 i Abstract ii List of Figures v Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Problem Statement 3 1.3 Thesis Organization 3 Chapter 2 Related Work 5 2.1 Exploring Collections of images 5 2.2 Routes, Videos, and Maps 7 2.3 Image Matching and Blending 9 Chapter 3 System Overview 12 Chapter 4 Google Street View and Map 15 4.1 Data from Google Street View 15 4.2 Data from Google Map 18 4.3 Trace along Google Street View by Information from Google Map 20 Chapter 5 Stitching Panorama Images 23 5.1 Preparing Data 23 5.2 Image Alignment and Matching 27 5.3 Image Blending and Stitching 32 Chapter 6 Generating Interactive Street View Video with Map 44 6.1 Generating Video 44 6.2 Integrating with Google Map 48 Chapter 7 Result 52 7.1 Result of the Guiding Video 52 7.2 Evaluation 55 7.3 Failure Cases 57 Chapter 8 Conclusion and Future Work 59 8.1 Conclusion 59 8.2 Future Work 59 Bibliography 61 | |
dc.language.iso | en | |
dc.title | 用於路線規劃的整合式平滑谷歌街景影片與地圖 | zh_TW |
dc.title | Integrated Smooth Google Street View Videos and Maps for Route Planning | en |
dc.type | Thesis | |
dc.date.schoolyear | 98-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 林奕成(I-Chen Lin),林文杰(Wen-Chieh Lin) | |
dc.subject.keyword | 谷歌,街景,影片,地圖,特徵,邊緣裁剪, | zh_TW |
dc.subject.keyword | Google,street view,video,map,feature,blending, boundary cut, | en |
dc.relation.page | 64 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2010-07-28 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
顯示於系所單位: | 資訊網路與多媒體研究所 |
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