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Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

Torna all'elenco Contributi in volume anno 2017

Contributo in volume

Tipo: Contributo in volume

Titolo: Technologies for visual localization and augmented reality in smart cities

Anno di pubblicazione: 2017

Formato: Elettronico Cartaceo

: Capitolo

Autori: Amato G.; Cardillo F.A.; Falchi F.

Affiliazioni autori: CNR-ISTI, Pisa, Italy

Autori CNR:

  • GIUSEPPE AMATO
  • FRANCO ALBERTO CARDILLO
  • FABRIZIO FALCHI

Lingua: inglese

Sintesi: The widespread diffusion of smart devices, such as smartphones and tablets, and the new emerging trend of wearable devices, such as smart glasses and smart watches, has pushed forward the development of applications where the user can interact relying on his or her position and field of view. In this way, users can also receive additional information in augmented reality, that is, seeing the information through the smart device, overlaid on top of the real scene. The GPS or the compass can be used to localize the user when augmented reality has to be provided with scenes of large size, for instance, squares or large buildings. However, when augmented reality has to be offered for enriching the view of small objects or small details of larger objects, for instance, statues, paintings, or epigraphs, a more precise positioning is needed. Visual object recognition and tracking technologies offer very detailed and fine-grained positioning capabilities. This chapter discusses the techniques enabling a precise positioning of the user and the subsequent experience in augmented reality, focusing on algorithms for image matching and homography estimation between the images seen by smart devices and images representing objects of interest.

Lingua sintesi: eng

Pagine da: 429

Pagine a: 434

Collana:

Geotechnologies and the environment Springer international
Paese di pubblicazione: Svizzera
Lingua: inglese
ISSN: 2365-0575

Titolo del volume: Sensing the Past: From artifact to historical site

N. volume della serie/collana: 16

Curatore/i del volume: Nicola Masini, Francesco Soldovieri

ISBN: 978-3-319-50518-3

DOI: 10.1007/978-3-319-50518-3_20

Editore: Springer International Publishing, Switzerland (CHE)

Referee: Sė: Internazionale

Stato della pubblicazione: Published version

Indicizzato da: ISI Web of Science (WOS) [000419729100021]

Parole chiave:

  • Localization
  • Augmented reality
  • Deep learning
  • Smart cities
  • Landmark recognition

URL: https://link.springer.com/chapter/10.1007%2F978-3-319-50518-3_20

Strutture CNR:

 
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