Sistema ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

 

Tesi etd-02022015-155548


Tipo di tesi
Tesi di laurea magistrale
Autore
GRAZIANO, ALESSANDRO
Indirizzo email
ale.graziano15@gmail.com
URN
etd-02022015-155548
Titolo
Robust visual hand pose estimation and tracking matching inverse kinematics on synergistic subspaces
Struttura
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA ROBOTICA E DELL'AUTOMAZIONE
Commissione
relatore Avizzano, Carlo Alberto
relatore Pollini, Lorenzo
relatore Prof. Ruffaldi, Emanuele
Parole chiave
  • Nessuna parola chiave trovata
Data inizio appello
19/02/2015;
Consultabilità
parziale
Data di rilascio
19/02/2018
Riassunto analitico
In this thesis a solution to the problem of recovering and tracking the 3D position, orientation and full articulation of a human hand from markerless visual observations obtained with a range camera is developed. The 3D tracking of human hands has a number of diverse applications including but not limited to human activity recognition, human-computer interaction, understanding human grasping, robot learning by demonstration , etc.
The method is based on an inverse kinematics scheme. The high dimensionality of the estimation problem is reduced by using the PCA (Principal Component Analisys) on a large dataset of human hand poses. The proposed method does not require special markers and/or a complex image acquisition setup. Being model based, it provides a continuous solution to the problem of tracking hand articulations.
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