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A Framework for Outdoor Mobile Augmented Reality and Its Application to Mountain Peak Detection

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Augmented Reality, Virtual Reality, and Computer Graphics (AVR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9768))

Abstract

Outdoor augmented reality applications project information of interest onto views of the world in real-time. Their core challenge is recognizing the meaningful objects present in the current view and retrieving and overlaying pertinent information onto such objects. In this paper we report on the development of a framework for mobile outdoor augmented reality application, applied to the overlay of peak information onto views of mountain landscapes. The resulting app operates by estimating the virtual panorama visible from the viewpoint of the user, using an online Digital Terrain Model (DEM), and by matching such panorama to the actual image framed by the camera. When a good match is found, meta-data from the DEM (e.g., peak name, altitude, distance) are projected in real time onto the view. The application, besides providing a nice experience to the user, can be employed to crowdsource the collection of annotated mountain images for environmental applications.

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Notes

  1. 1.

    http://www.lonelyplanet.com/guides.

  2. 2.

    http://www.wikitude.com/app/.

  3. 3.

    A detailed description of the offline algorithms can be found in [8, 10].

  4. 4.

    http://snowwatch.polimi.it/?lang=en.

  5. 5.

    The data set is available at http://snowwatch.polimi.it.

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Acknowledgment

This work has been partially funded by European Commission and by the Lombardy Region through the PROACTIVE FESR Project (http://www.proactiveproject.eu) and by the FP7 CHEST Project (http://www.chest-project.eu) open call grant.

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Correspondence to Roman Fedorov .

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Fedorov, R., Frajberg, D., Fraternali, P. (2016). A Framework for Outdoor Mobile Augmented Reality and Its Application to Mountain Peak Detection. In: De Paolis, L., Mongelli, A. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2016. Lecture Notes in Computer Science(), vol 9768. Springer, Cham. https://doi.org/10.1007/978-3-319-40621-3_21

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  • DOI: https://doi.org/10.1007/978-3-319-40621-3_21

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