Title

以BIM與影像辨識為基礎之室內空間辨識雛型系統

Translated Titles

BIM-Vision-Based Indoor Localization Prototype

DOI

10.6846/TKU.2012.00380

Authors

邱政銘

Key Words

室內定位空間辨識 ; 工業基礎類別 ; 影像辨識 ; Indoor LocalizationIndoor Localization ; IFC ; Image Recognition ; BIM

PublicationName

淡江大學土木工程學系碩士班學位論文

Volume or Term/Year and Month of Publication

2012年

Academic Degree Category

碩士

Advisor

蔡明修

Content Language

繁體中文

Chinese Abstract

本研究宗旨在使用室內空間特徵影像做為辨識標籤並結合建築資訊模型(Building Inform-ation Modeling)內所包含的空間資訊,目的是為了提供一個經濟的室內空間定位技術,使用戶可以透過智慧型手持裝置相機鏡頭擷取所在位置的空間特徵影像,得知目前所在位置及該空間資訊。 其方法和目前無線頻寬(Wireless)和無線射頻(Radio Frequency IDentification)室內定位技術有所不同,本研究應用的室內空間特徵影像做為位置識別標籤技術。其架構包括三個功能模組,(1)空間特徵影像資料庫,(2)空間特徵影像管理模組,(3)空間特徵影像辨識定位模組。空間特徵影像資料庫是從建築資訊模型(Building Information Modeling)收集來自工業基礎類別標準(Industry Fo-undation Classes)相關空間資訊及相對應空間的特徵影像。空間特徵影像管理模組為拍攝空間特徵影像,與資料庫連結並建立空間特徵影像集。空間特徵影像辨識定位模組是使用擴增實境技術,運用D'fusion軟體的影像辨識技術,透過手持裝置擷取所在空間特徵影像,進行影像辨識定位後,連結到資料庫將所在空間資訊顯示在手持裝置上。 結果與討論是以BIM與影像辨識為基礎之空間辨識雛型系統,透過智慧型手持裝置的攝影鏡頭在Android平台上運行,如智慧型手機和平板電腦。透過不斷的技術測試,以了本研究的技術的可行性。根據多次測試結果,本研究室內定位雛型系統可以識別空間位置及使用者所在的空間資訊,然而當室內空間是缺乏特徵影像而無法辨識時,如室內空間為單調的牆壁及相似度過高,未能被識別。為了克服這種情況,將以二維空間標籤的QR碼(Quick Response Code),替代空間特徵影像作為辨識標籤。此外,由於空間資訊是從現有的建築資訊模型而來的,可以保證資訊的一致性。之後並透過經濟可行性進行分析評估其成本與效益。

English Abstract

Purpose In order to provide an economical indoor location detective technique, this study is aimed to use photo images as the indoor spatial identification tags associated with the spatial information of the existing building information model (BIM), so that users can identify their locations via the camera on mobile device based on the real images. Method Unlike the wireless and RFID-based indoor positioning techniques, this study applied the image recognition technique to indoor location detection. Prototype architecture includes three functional modules, namely, (1) Spatial image database, (2) spatial image management module, and (3) vision-based localization module are developed. The spatial image database is the data collection of space related data from the IFC (Industry Foundation Classes) dataset of the existing BIM and space feature image data collected form users. The spatial image management module provides users an interface to collect the spatial photo images of buildings, and bind them with the location data from the spatial image database. Then, the vision-based localization module developed based on the D’fusion studio can identify the space location by recognizing the images from the vision captured with the camera on a smart phone, and the corresponding spatial data can be retrieved from the database. Results & Discussion The BIM-Vision-Based indoor localization prototype was developed as an android platform application running on the mobile device with imbedded camera such as smart phones and tablets. Technique feasibility is continuously tested in current phase. According to the basic test results, the prototype can identify the indoor locations of decorated spaces; however, once the indoor spaces are lack of recognition features, such as the empty spaces with blank and monotony walls, the recognition function failed. To overcome this defect, the Quick Response (QR) code, the trademark for a type of two-dimensional code, is used as a substitution of the photos for this prototype. Besides, since the location data is transferred from the existing building information model, the data consistency can be ensured. In the future, the economic feasibility of this prototype would be analyzed to evaluate the cost and benefit ration.

Topic Category 工學院 > 土木工程學系碩士班
工程學 > 土木與建築工程
Reference
  1. cy-navigation-system for complex buildings,” Tsinghua
    連結:
  2. Localization for Blind Pedestrian Navigation
    連結:
  3. 10.Corporation, G., “About GPS,” Website, 2001,
    連結:
  4. 14.Ni, L. M., Y. Liu, Y. C. Lau and A. P. Patil, “LANDMARC: Indoor Location Sensing Using Active RFID,” Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003, pp.407-415.
    連結:
  5. 16.Bahl, P. and V. N. Padmanabhan, “RADAR: An Inbuilding RF-based UserLocation and Tracking System,” Proceeding of IEEE INFOCOM, 2000,Vol.2, pp.775-784.
    連結:
  6. 17.Bahl, P., V. N. Padmanabhan, and A. Balachandran, “Enhancements to the RADAR User Location and Tracking System”, Microsoft Research Technical Report, 2000.
    連結:
  7. 22.Milgram, P., Takemura, H., Utsumi, A. and Kishino, F., “Augmented Reality: A Class of Displays on the Reality-Virtuality Continuum,” Telemanipulator and Telepresence Technologies, SPIE Proceedings Vol. 2351, pp. 282-292, November, 1994.
    連結:
  8. 23.Azuma, R., “A Survey of Augmented Reality,” Presence: Teleoperators and Virtual Environments, Vol. 6, No. 4, pp. 355-385, August 1997.
    連結:
  9. 28.Yuana, M.L., Ongb, S.K., Nee, A.Y.C., “A Generalized Registration Method for Augmented Reality Systems,” Computers & Graphics Vol. 29, Issue 6, pp. 980-997, December, 2005.
    連結:
  10. 1.Rueppel,U.andStuebbe,K.M.(2008)“BIM-basedindoor-emergen-
  11. Science & Technology,13, 362–367.
  12. 2.Treuillet, S., Royer, E., Jovanova, B., Arsov, I., Preda,
  13. M., Preteux, F., Durette, B., Aleysson, J. H., D., and
  14. Dramas, F. (2010) “Outdoor/Indoor Vision-Based
  15. Assistance,” International Journal of Image and
  16. Graphics, 10(4), 481–496.
  17. 3.Liebich , T., 2009. IFC 2x Edition 3 Model Implementation Guide, building SMART International Modeling Support Group.
  18. 4.蔡志偉,2007。IFC建築資訊內容應用於結構分析資料擷取,國立交通大學土木工程學系碩士論文。
  19. 5.Liebich, T., Adachi, Y., Forester, J., Hyvarinen, J., Richter, S., C-hipman, T., Wix, J., 2009,IFC2x Edition 4 beta 2 version, buildingSMART International Limited.
  20. 6.徐業良,2005.設計幾何模型的建構,元智大學機械系大三機械設計課程教材。
  21. 7.林士傑,2011。以WIFI網路為基礎的追蹤系統之研究,銘傳大學傳播工程學系碩士論文。
  22. 8.楊修武,2008。高山症救援行動定位服務系統雛型設計,國立陽明大學生物醫學資訊研究所碩士論文。
  23. 9.曲威光,2004。通訊科技與多媒體產業,新陸書局股份有限公司,
  24. http://www.garmin.com/about GPS/.
  25. 11.Want, R., A. Hopper, V. Falcao, J. Gibbons, “The Active Badge Location System,1992,”ACM Transaction on Information Systems”, Vol.40, No.1, pp.91-102.
  26. 12.Priyantha, N. B., A. Chakraborty and H. Balakrishnan, “The Cricket
  27. Location-Support System,” Proceeding of the 6th ACM MOBICOM, 2000,pp.32-43.
  28. 13.Ward, A., P. Osborn, J. Newman and S. Hodges, “The Bat UltrasonicLocation System,” 1997, http://www.uk.research.att.com/bat/.
  29. 15.Orr, R.J. and G.D. Abowd, “The Smart Floor: A Mechanism for NaturalUser Identification and Tracking,” Proc. 2000 Conf. Human Factors inComputing Systems, ACM Press, New York, 2000.
  30. 18.Orr, R.J. and G.D. Abowd, “The Smart Floor: A Mechanism for Natural User Identification and Tracking,” Proc. 2000 Conf. Human Factors in Computing Systems, ACM Press, New York, 2000.
  31. 19.Sutherland, I. E., “The Ultimate Display,” Proceedings of IFIP Congress, pp. 506-508, 1965.
  32. 20.Samset, E., Schmalstieg, D., Sloten, J. V., Freudenthal, A., Declerck, J., Casciaro, S., Rideng, O., Gersak, B., “Augmented Reality in Surgical Procedures,” Proceedings of SPIE Medical Imaging, Vol. 6806, Issue 1, pp. 68060K-68060K-12, February, 2008.
  33. 21.Fischer, J., Neff, M., Freudenstein D. and Bartz1, D., “Medical Augmented Reality Based on Commercial Image Guided Surgery,” Eurographics Symposium on Virtual Environments, pp. 83-86, 2004.
  34. 24.Kato, H. and Billinghurst, M., “Marker Tracking and HMD Calibration for a Video-Based Augmented Reality Conferencing System,” in IWAR ’99: Proceedings of the 2nd, IEEE and ACM International Workshop on Augmented Reality, pp. 85-94, IEEE Computer Society, 1999.
  35. 25.QR Code.com, http://www.denso-wave.com/qrcode/index-e.html
  36. 26.QR-Code Generator, http://qrcode.kaywa.com/
  37. 27.Gordon, I. and Lowe, D. G., “Scene Modeling, Recognition and Tracking with Invariant Image Features,” International Symposium on Mixed and Augmented Reality (ISMAR), Arlington, VA, pp. 110-119, 2004.
  38. 29.ARToolKit, http://www.hitl.washington.edu/artoolkit/
  39. 30.ARToolKit Professional, http://www.artoolworks.com/
  40. 31.Metaio, http://www.metaio.com/
  41. 32.Metaio Unifeye SDK, http://www.metaio.com/ /products/sdk/
  42. 33.PITOECH CO.,LTD., http://www.pitotech.com.tw
  43. 34.D'Fusion, http://www.t-immersion.com/
  44. 35.Liu, H., Darabi, H., Banerjee, P. and Liu, J. (2007) “Survey of Wireless Indoor Positioning Techniques and Systems”, IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews, 37(6), 1067-1080.
  45. 36.Lopez, Y.A., Cos Gomez, M.E., Alvarez, J.L., Andres, F.L.H. (2011) “Evaluation of an RSS-based indoor location system”, Sensors and Actuators, Vol.167, 110–116.
  46. 37.Augmented.org,http://www.augmented.org/blog/2011/09/making-the-digital-a-natural-experience-the-insidear-2011/
Times Cited
  1. 黃朝雍(2014)。BIM-based環景檢視系統建置與應用之研究。臺北科技大學土木與防災研究所學位論文。2014。1-84。