GHOUAIEL, Nehla; CIEUTAT, Jean Marc; JESSEL, Jean Pierre

doi:10.1007/978-3-319-04702-7

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GHOUAIEL, Nehla
ESTIA INSTITUTE OF TECHNOLOGY

CIEUTAT, Jean Marc
ESTIA INSTITUTE OF TECHNOLOGY

JESSEL, Jean Pierre

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Chapitre d'ouvrage

Ce document a été publié dans

Intelligent Systems for Science and Information: Extended and Selected Results from the Science and Information Conference 2013. 2014-02-07, vol. 542, p. 139-151

Springer

Résumé en anglais

Although human's sedentary nature over time, his wish to travel the world remains as strong as ever. This paper discusses how imagery and Augmented Reality (AR) techniques can be of great help not only when discovering a new urban environment but also when observ-ing the evolution of the natural environment. The study is applied on Smartphone which is currently our most familiar device. Smart phone is utilized in our daily lives because it is low weight, ease of communications, and other valuable applications. In this chapter, we discuss technical issues of augmented reality especially with building recognition. Our building recog-nition method is based on an efficient hybrid approach, which combines the potentials of Speeded Up Robust Features (SURF) features points and lines. Our method relies on Approxi-mate Nearest Neighbors Search approach (ANNS). Although ANNS approaches are high speed, they are less accurate than linear algorithms. To assure an optimal trade-off between speed and accuracy, the proposed method performs a filtering step on the top of the ANNS. Finally, our method calls Hausdorff measure [15] with line models.< Réduire

Mots clés en anglais

Mobile Augmented Reality

Building Recognition

Machine Vision