Abstract
This paper proposes a scalable building facade recognition and tracking system for outdoor augmented reality enabling real time augmentation of various information onto the facade. The system is composed of three modules: recognition and tracking module, server-client module and GPS module. In the recognition and tracking module, Generic Random Forest was used for real time recognition and three-dimensional pose estimation of facades. For scalable recognition, global region is divided into multiple local regions and then, same regional buildings are trained separately into a forest. In the server-client module, client maintains own travel map in order to choose proper forest by employing GPS sensor, and server transmits a new forest when client detects never visited regions. This makes our system scalable and also expansible to new regions.
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Acknowledgments
This work was supported by the IT R&D program of MKE/MCST/IITA, [10039165, Development of learner-participational and interactive 3D Virtual learning contents technology]. This work was also supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (MEST) (2011-0013776).
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Lee, S., Seo, YH., Yang, H.S. (2013). Scalable Building Facade Recognition and Tracking for Outdoor Augmented Reality. In: Park, J., Barolli, L., Xhafa, F., Jeong, HY. (eds) Information Technology Convergence. Lecture Notes in Electrical Engineering, vol 253. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_97
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DOI: https://doi.org/10.1007/978-94-007-6996-0_97
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