Smartphone technology with embedded cameras, sensors, and powerful computational resources have made mobile Augmented Reality possible. In this paper, we present i-Street, an Android touristic application whose aim is to detect, identify and read the street plates in a video flow and then to estimate relative pose in order to accurately augment them with virtual overlays. The system was successfully tested in the historical centre of Grenoble (France), proving to be robust to outdoor illumination conditions and to device pose variance. The average identification rate in realistic laboratory tests was about 82%, remaining cases were rejected with no false positives.

i-Street: Detection, identification, augmentation of street plates in a touristic mobile application

Messelodi, Stefano;Modena, Carla Maria;Porzi, Lorenzo;Chippendale, Paul Ian
2015

Abstract

Smartphone technology with embedded cameras, sensors, and powerful computational resources have made mobile Augmented Reality possible. In this paper, we present i-Street, an Android touristic application whose aim is to detect, identify and read the street plates in a video flow and then to estimate relative pose in order to accurately augment them with virtual overlays. The system was successfully tested in the historical centre of Grenoble (France), proving to be robust to outdoor illumination conditions and to device pose variance. The average identification rate in realistic laboratory tests was about 82%, remaining cases were rejected with no false positives.
978-3-319-23233-1
978-3-319-23234-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/300816
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