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Abstract
In this thesis is presented the development of a munti-object detection and tracking
method in a low light dynamic environment. After a brief introduction on the
history of tracking and a general description of the procedure, the following chapters
continue with a list of the most used methods to satisfy the solution of the tracking
problem, giving greater importance to those that have been taken into consideration
for the solution of our specific problem. After this introduction, a description of the
dynamic environment, in which our target objects will have to be traced, is provided.
This will lead us to the presentation of the approach used to achieve the goal of
tracking bumper cars inside an interactive carousel.
Abstract
In this thesis is presented the development of a munti-object detection and tracking
method in a low light dynamic environment. After a brief introduction on the
history of tracking and a general description of the procedure, the following chapters
continue with a list of the most used methods to satisfy the solution of the tracking
problem, giving greater importance to those that have been taken into consideration
for the solution of our specific problem. After this introduction, a description of the
dynamic environment, in which our target objects will have to be traced, is provided.
This will lead us to the presentation of the approach used to achieve the goal of
tracking bumper cars inside an interactive carousel.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Villa, Giacomo Maria
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
object detection,object tracking,convolutional newral network
Data di discussione della Tesi
10 Marzo 2021
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(NON SPECIFICATO)
Autore della tesi
Villa, Giacomo Maria
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
object detection,object tracking,convolutional newral network
Data di discussione della Tesi
10 Marzo 2021
URI
Gestione del documento: