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Tesi etd-11252018-224303


Thesis type
Tesi di laurea magistrale
Author
KERTUSHA, INDRIT
URN
etd-11252018-224303
Title
Design and Implementation of a System Based on Deep Convolutional Networks for Intelligent Visual Surveillance
Struttura
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
COMPUTER ENGINEERING
Commissione
relatore Gennaro, Claudio
relatore Falchi, Fabrizio
relatore Amato, Giuseppe
Parole chiave
  • Deep convolutional networks
  • object detection
  • face recognition
Data inizio appello
11/12/2018;
Consultabilità
completa
Riassunto analitico
The theme of public safety, in light of the latest dramatic events, has recently become a relevant aspect, especially in large urban areas. The possibility to act promptly in case of dangers or alarms can be of fundamental importance in determining the favorable outcome of the interventions. For example, identifying and tracking an individual or a suspicious vehicle that moves in an urban context may require significant deployment of forces, with costs that can sometimes render the interventions ineffective.
The intelligent camera represents a technology that can help manage this problem and that in recent years has seen a rapid development in many directions. The most interesting aspect is certainly its low cost. Furthermore, the advent of the 5G network and its integration with drone technology could provide a synergy for the development of innovative and low-cost public security applications. The visual information detected by the camera (photo and video) can be effectively exploited in the phase of identification on the ground, through the use of artificial intelligence technologies based on deep learning. The development of these technologies has been enormous as well. Thanks to the power of graphics cards equipped with Graphics Processing Units (GPU), recognizing in real time, in a video, a face of a person or a specific object in motion is now within the reach of a home computer.
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