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http://dx.doi.org/10.7319/kogsis.2013.21.2.035

A Study on the Building Object Correspondence Between SLI and Vector Map for Conflation  

Ga, Chill O (Department of Civil & Environmental Engineering, Seoul National University)
Rho, Gon Il (Department of Civil & Environmental Engineering, Seoul National University)
Huh, Yong (Seoul National University Engineering Research Institute)
Lee, Jeung Ho (Seoul National University Engineering Research Institute)
Yu, Ki Yun (Department of Civil & Environmental Engineering, Seoul National University)
Publication Information
Journal of Korean Society for Geospatial Information Science / v.21, no.2, 2013 , pp. 35-43 More about this Journal
Abstract
Georeferenced SLI(Street-Level Imagery) services such as Google Streetview, which contain abundant information about the real world, can increase its applicability substantially through conflation with other spatial datasets. For this purpose, we propose a method to improve a correspondence of building region to combine building information more accurately. First, the spatial inconsistency between SLI and vector map is removed by alignment based on road intersections. Then, visible building regions are searched from the spatial inconsistency-removed vector map, and the optimal corresponding building areas are determined in the SLI scene using the visible regions as seed information. The experimental results demonstrated that our method had improved the accuracy of building region correspondence by about 8%. Therefore, our method can be utilized effectively for enhancement of conflation service based on the SLI.
Keywords
SLI(Street-Level Imagery); Vector Map; Conflation; ISOVIST;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 Google, 2013, Google Maps, http://maps.google.co.kr.
2 Naver, 2013, Naver Map, http://map.naver.com.
3 Daum, 2013, Daum Map, http://local.daum.net.
4 Anguelov, D., Dulong, C., Filip, D., Frueh, C., Lafon, S., Lyon, R., Ogale, A., Vincent, L., and Weaver, J., 2010, Google street view: capturing the world at street level, IEEE Computer, Vol.43, No. 6, pp. 32-38.   DOI   ScienceOn
5 Benedikt, M. L., 1979, To take hold of space: isovist and isovist field, environment and planning B, Vol. 6, pp. 47-65.   DOI
6 Canny, J., 1986, A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, pp. 679-698.
7 Chen, C. C., Knoblock, C. A., and Shahabi, C., 2006B, Automatically conflating road vector data with orthoimagery, GeoInformatica, Vol.10, No. 4, pp. 495-530.   DOI   ScienceOn
8 Fischler, M. A. and Bolles, R. C., 1981, Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Communica-tions of the ACM, Vol. 24, No. 6, pp. 381-395.   DOI   ScienceOn
9 Ga, C., Lee, J. H., Yang, S. C., Yu, K., 2012, The removal of spatial inconsistency between SLI and 2D map for conflation, Journal of the Korean society for geo-spatial information system, Vol. 20, No. 2, pp. 63-71.   과학기술학회마을   DOI   ScienceOn
10 Hammoudi, K., Dornaika, F., Soheilian, B. and Paparoditis, N., 2010, Extracting wire-frame models of street facades from 3D point clouds and the corresponding cadastral map, IAPRS, Vol. 38, Part 3A, pp. 91-96, Saint-Mande, France.
11 Juan J. Ruiz, F. Javier Ariza, Manuel A. Urena, Elidia B. Blazquez, 2011, Digital map conflation: a review of the process and a proposal for classification. International Journal of Geographical Information Science, Vol. 25, No. 9, pp. 1439-1466 (2011).   DOI   ScienceOn
12 Pylvanainen, T., Roimela, K., Vedantham, R., Itaranta, J., Wang, R.S., Grzeszczuk, R., 2010, Automatic alignment and multi-view segmentation of street view data using 3D shape priors, In Symposium on 3D Data Processing, Visualization and Transmission, Paris, France.
13 Yuan, S. and Tao, C., 1999, Development of conflation components, The Proceedings of Geoinforma-tics'99 Conference, Ann Arbor, USA, pp. 1-13.
14 Rafael C. Gonzales and Richard E. Woods, Digital image processing, Second Edition, Prentice Hall, 2002.
15 Samal, A., Seth, S., and Cueto, K., 2004, A featurebased approach to conflation of geospatial sources, International Journal of Geographical Information Science, Vol. 18, No. 5, pp. 459-489.   DOI   ScienceOn