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Maps with 3D visual models are becoming a remarkable feature of 3D map services. High-resolution image data is obtained for the construction of 3D visualized models.The3D map not only provides the capabilities of 3D measurements and knowledge mining, but also provides the virtual experienceof places of interest, such as demonstrated in the Google Earth. Applications of 3D maps are expanding into the areas of architecture, property management, and urban environment monitoring. However, the reconstruction of high quality 3D models is time consuming, and requires robust hardware and powerful software to handle the enormous amount of data. This is especially for automatic implementation of 3D models and the representation of complicated surfacesthat still need improvements with in the visualisation techniques. The shortcoming of 3D model-based maps is the limitation of detailed coverage since a user can only view and measure objects that are already modelled in the virtual environment. This paper proposes and demonstrates a 3D map concept that is realistic and image-based, that enables geometric measurements and geo-location services. Additionally, image-based 3D maps provide more detailed information of the real world than 3D model-based maps. The image-based 3D maps use geo-referenced stereo images or panoramic images. The geometric relationships between objects in the images can be resolved from the geometric model of stereo images. The panoramic function makes 3D maps more interactive with users but also creates an interesting immersive circumstance. Actually, unmeasurable image-based 3D maps already exist, such as Google street view, but only provide virtual experiences in terms of photos. The topographic and terrain attributes, such as shapes and heights though are omitted. This paper also discusses the potential for using a low cost land Mobile Mapping System (MMS) to implement realistic image 3D mapping, and evaluates the positioning accuracy that a measureable realistic image-based (MRI) system can produce. The major contribution here is the implementation of measurable images on 3D maps to obtain various measurements from real scenes.
Rocznik
Tom
Strony
297--310
Opis fizyczny
Bibliogr. 15 poz.
Twórcy
autor
- School of Surveying and Spatial Information Systems, University of New South Wales, Sydney, NSW 2052, Australia
autor
- School of Surveying and Spatial Information Systems, University of New South Wales, Sydney, NSW 2052, Australia
autor
- Faculty of Engineering and Information Technology, University of Technology, Sydney PO Box 123 Broadway, Ultimo, NSW 2007, Australia
autor
- School of Surveying and Spatial Information Systems, University of New South Wales, Sydney, NSW 2052, Australia
autor
- School of Surveying and Spatial Information Systems, University of New South Wales, Sydney, NSW 2052, Australia
Bibliografia
- 1.Cramer, M. & Stallmann, D.,2001. On the Use of GPS/Inertial Exterior Orientation Parameters in Airborne Photogrammetry, Proceedings of the OEEPE Workshop, Integrated Sensor Orientation, Hanover, Germany, 17–18 September.
- 2.Ellum, C.& El-Sheimy, N., 2002. Land-based Mobile Mapping Systems. Photogrammetric Engineering and Remote Sensing, vol.68, no.1, pp.13–17.
- 3.Gledhill, D., Tian, G.Y., Talor, D. & Clarke, D., 2003. Panoramic Imaging--AReview. Computers & Graphics, vol. 27, no. 3, pp. 435-445.
- 4.Hu, Q., Liu, S. & Mao, K., 2009. A “Reality Vision” Navigation Technique Based on Sequence Geo Referenced Image Databases, Critical Issues in Transportation Systems Palnning, Development and Management, ASCE.
- 5.Hu,Q. & Wang, H., 2008. A New Web-based Geo-information Service Approach With Digital Measurable Image Toward Direct Virtual Reality. ISPRS Congress Beijing 2008, Commission IV, WG IV/5.
- 6.Luhmann, T., Robson, S., Kyle, S. & Harley, I., 2006. Close range Photogrammetry: Principles, Techniques and Applications, Whittles,United Kingdom.
- 7.Li, D., Huang, J. & Shao, Z., 2008. Digital Earth with Digital Measurable Images. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. vol. XXXVII, part no. B4.
- 8.Li, D. & Shen, X. , 2009. Geospatial Information Service Based on Digital Measurable Image. Geo- Spatial Information Science , vol. 13, no. 2, pp. 79-84.
- 9.Li, D., Wang, M. & Gong, J. , 2002. Principle and Implement of Measurable Virtual Reality (MVR) Based on Seamless Stereo-orthoimage Database. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. vol. XXX IV, part no. 5/W3.
- 10.Li, X., Wang. J., Olesk, A., Knight, N. & Ding, W., 2010. Indoor Positioning within a Single Camera and 3D Maps. Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS), Helsinki, Finland.
- 11.Lowe, D.G., 2004. Distinctive Image Features from Scale-invariant Keypoints. International Journal of Computer Vision, vol.60, no.2,pp.91-110.
- 12.Madeira, S., Gonçalves J. & Bastos, L., 2007. Implementation of A Low Cost Mobile Mapping System. 5th International Symposium on Mobile Mapping Technology, Padua, Italy.
- 13.Madeira, S., Gonçalves, J. & Bastos, L.,2010. Photogrammetric Mapping and Measuring Application Using MATLAB. Computers & Geosciences, vol.36, no.6, pp.699-706.
- 14.Olesk, A., & Wang, J., 2009. Geometric and Error Analysis for 3D Map matching.International Global Navigation Satellite Systems Society, IGNSS Symposium 2009, Australia.
- 15.Otani, H., Aoki, H., Ito, T. & kochi, N., 2004. 3D Model Measuring System. The International Archives of Photogrammetry and Remote Sensing, Commission V, WG V/2.
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-b72ca689-a6ee-40e0-b3ac-c0f2b8394098