| dc.description.abstract | This thesis work is focused on two applicative fields of image processing research,
which, for different reasons, have become particularly active in the last decade: Mixed
Reality and Biometry. Though the image processing techniques involved in these two
research areas are often different, they share the key objective of recognizing salient
features typically captured through imaging devices.
Enabling technologies for augmented/mixed reality have been improved and refined
throughout the last years and more recently they seems to have finally passed the demo
stage to becoming ready for practical industrial and commercial applications. To this
regard, a crucial role will likely be played by the new generation of smartphones and
tablets, equipped with an arsenal of sensors connections and enough processing power
for becoming the most portable and affordable AR platform ever. Within this context,
techniques like gesture recognition by means of simple, light and robust capturing
hardware and advanced computer vision techniques may play an important role in
providing a natural and robust way to control software applications and to enhance onthe-
field operational capabilities. The research described in this thesis is targeted toward
advanced visualization and interaction strategies aimed to improve the operative range
and robustness of mixed reality applications, particularly for demanding industrial
environments... [edited by Author] | it_IT |
