Outdoor environment monitoring with unmanned aerial vehicles

This work addresses the problem of video surveillance of out- door environments with unmanned aerial vehicles (UAV). Speci_cally it proposes a two-step approach, with an initial o_ine stage in which a mosaic of the zone to be monitored is built from video sequences. The second step tackles with the problem of online detection of relevant dif- ferences between the acquired images and the mosaic model. A GPS- assisted approach is proposed to deal with e_ciency issues in this online step. Experimental results prove that the proposed approach can be used to detect relevant changes in the speci_c case of road safety assurance in dangerous zones.

uav outdoor monitoring area

C. Piciarelli, C. Micheloni, N. Martinel, M. Vernier, G.L. Foresti, Outdoor environment monitoring with unmanned aerial vehicles, International Conference on Image Analysis and Processing (ICIAP), Naples, Italy, September 9-13, 2013.

Remote Feature Learning for Mobile Re-Identification

This work introduces a novel method for person re-identification using embedded smart cameras. State-of-theart methods address the re-identification problem using global and local features, metric learning and feature transformation algorithms. Such methods require advanced systems with high computational capabilities. Nowadays, there is a growing interest in security applications using embedded cameras. Motivated by this we propose to study a new system that addresses the challenges posed by the reidentification problem using devices (e.g. smartphones, etc.) that have limited resources. In this work we introduce a novel client-server system that exploits a feature learning method to achieve a two-fold objective: (i) maximize the re-identification performance over time and (ii) reduce the required computational costs. In the training phase, state-of-the-art features are selected considering both the device capabilities and re-identification performance. During the detection phase, the re-identification performance are maximized by selecting the best features for a given input image. To demonstrate the performance of the proposed method we conduct the experiments using different mobile devices. Statistics about feature extraction and feature matching are presented together with re-identification results.

system architecture

M. Vernier, N. Martinel, C. Micheloni, G.L. Foresti, Remote Feature Learning for Mobile Re-Identification, International Conference on Distributed Smart Cameras, Palm Spring CA, USA, October 29 – November 1, 2013.

 

Image Processing Supports HCI in Museum Application

This work introduces a novel information visualization technique for mobile devices through Augmented Reality (AR). A painting boundary detector and a features extraction modules have been implemented to compute paintings signatures. The computed signatures are matched using a linear weighted combination of the extracted features. The detected boundaries and the features are exploited to compute the homography transformations. The homography transformations are used to introduce a novel user interaction technique for AR. Three different user interfaces have been evaluated using standard usability methods.

painting recognized by the proposed system

Martinel, N.; Vernier, M.; Micheloni, C. and Piciarelli, C., Image Processing Supports HCI in Museum Application. In International Conference on Computer Vision Theory and Applications, Barcelona Spain 2012.

 

Geobashing | A new dimension in mobile gaming

Cos’è Geobashing

Geobashing è un Massively Multiplayer Online Gaming (MMOG) sviluppato dal gruppo “Pervasive Computing group” appartenente alla facoltà di “Technical Sciences” dell’università Alpen Adria di Klagenfurt (Austria).

Geobashing si suddivide principalmente in due tipi di gioco:

  • sfide (challenges) e
  • combattimenti (fights).

Le sfide sono semplici “prove” che permettono ad un singolo giocatore di sfidare i migliori tempi migliori effettuati da altri giocatori. Per esempio una prova potrebbe consistere in una sfida di corsa leggera dove il giocatore deve percorrere un determinato percorso e battere il record imposto da un altro avversario.

I combattimenti invece sono delle vere e proprie sfide tra due soli giocatori. Un giocatore decide di attaccare un altro partecipante che si trova nelle vicinanze: sarà il sistema di Geobashing stesso poi a decidere chi sarà il vincitore (tenendo conto ovviamente di altri parametri e punteggi collezionati nei precedenti combattimenti).

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My Erasmus

L’erasmus (European Region Action Scheme for the Mobility of University Students) è un progetto universitario Europeo che permette allo studente di effettuare un periodo di studio legalmente riconosciuto in una qualsiasi università straniera.

Il mio Erasmus è durato sei mesi e la città scelta è stata Klagenfurt in Austria. Questa decisione è stata principalmente condizionata dal Double Degree Program, un programma di studio internazionale offerto dalla mia università.

Questa esperienza è stata indimenticabile. Consiglio a tutti la città di Klagenfurt come meta Erasmus e soprattutto l’Alpen Adria Universitat, una università organizzata che offre agli studenti numerosi servizi ed opportunità di studio.

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