Abstract
This paper describes a positioning algorithm for mobile phones based on image recognition. The use of image recognition based (IRB) positioning in mobile applications is characterized by the availability of a single camera for estimate the camera position and orientation. A prior knowledge of 3D environment is needed in the form of a database of images with associated spatial information that can be built projecting the 3D model on a set of synthetic solid images (range + RGB images). The IRB procedure proposed by the authors can be divided in two steps: the selection from the database of the most similar image to the query image used to locate the camera and the estimation of the position and orientation of the camera based on available 3D data on the reference image. The MPEG standard Compact Descriptors for Visual Search (CDVS) has been used to reduce hugely the processing time. Some practical results of the location methodology in outdoor environment have been described in terms of processing time and accuracy of position and attitude.
Chapter PDF
Similar content being viewed by others
References
Nishkam, R., Pravin, S., Andrew, F., Ahmed, E., Liviu, I.: Indoor localization using camera phones. In: Mobile Computing Systems and Applications (2006)
Mautz, R., Tilch, S.: Survey of optical indoor positioning systems. In: International Conference on Indoor Positioning and Indoor Navigation (IPIN), September 21-23, 2011
Biswas, J., Veloso, M.: WiFi localization and navigation for autonomous indoor mobile robots. In: International Conference on Robotics and Automation (2010)
Chung, L., Donahoe, M., Schmandt, C., Kim, I., Razavai, P., Wiseman, M.: Indoor location sensing using geomagnetism. In: Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services, pp. 141–154 (2011)
Schneegans, S., Vorst, P., Zell, A.: Using RFID snapshots for mobile robot self-localization. In: European Conference on Mobile Robots (2007)
Hong-Shik, K., Jong-Suk, C.: Advanced indoor localization using ultrasonic sensor and digital compass. In: International Conference on Control, Automation and Systems (2008)
Kitanov, A., Biševac, S., Petrović, I.: Mobile robot self-localization in complex indoor environments using monocular vision and 3D model. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Zürich, Switzerland (2007)
Piras, M., Dabove, P., Lingua, A.M., Aicardi, I.: Indoor navigation using smartphone technology: a future challenge or an actual possibility? In: IEEE/ION Position, Location Proceedings of the and Navigation Symposium, May 5-8, 2014
Lingua, A.M., Aicardi, I., Ghinamo, G., Francini, G., Lepsoy, S.: The MPEG7 visual search solution for image recognition based positioning using 3D models. In: Proceedings of the 27th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 2014), September 8-12, 2014
CDVS. ISO/IEC DIS 15938-13 Compact Descriptors for Visual Search (2014)
McGlone, C. (ed.): Manual of Photogrammetry, 5th edn., pp. 280–281. ASPRS
Bornaz, L., Dequal, S.: A new concept: the solid image. In: CIPA 2003 Proceedings of XIXth International Symposium, pp. 169–174 (2003)
PCT/EP2011/050994 Method and system for comparing images
Lowe, D.: Distinctive image features from scale-invariant keypoints. International, Journal of Computer Vision 60(2), 91–110 (2004)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, March 2004
Karara, H.M. (ed.): Non Topography Photogrammetry, 2nd edn., pp. 46–48. ASPRS
De Agostino, M., Lingua, A., Marenchino, D., Nex, F., Piras, M.: GIMPHI: a new integration approach for early impact assessment. Applied Geomatics 3(4), 241–249. ISSN 1866-9298
Fusiello, A.: Visione computazionale. Tecniche di ricostruzione tridimensionale (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Ghinamo, G., Corbi, C., Lovisolo, P., Lingua, A., Aicardi, I., Grasso, N. (2015). Accurate Positioning and Orientation Estimation in Urban Environment Based on 3D Models. In: Murino, V., Puppo, E., Sona, D., Cristani, M., Sansone, C. (eds) New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops. ICIAP 2015. Lecture Notes in Computer Science(), vol 9281. Springer, Cham. https://doi.org/10.1007/978-3-319-23222-5_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-23222-5_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23221-8
Online ISBN: 978-3-319-23222-5
eBook Packages: Computer ScienceComputer Science (R0)