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Digital archive of theses discussed at the University of Pisa

 

Thesis etd-01242022-112016


Thesis type
Tesi di laurea magistrale
Author
MAODDI, EMILIO
URN
etd-01242022-112016
Thesis title
Development of a multi-camera system for the estimation of body segments volume aimed at cardiac insufficiency risk assessment
Department
INGEGNERIA DELL'INFORMAZIONE
Course of study
INGEGNERIA ROBOTICA E DELL'AUTOMAZIONE
Supervisors
relatore Prof. Avizzano, Carlo Alberto
relatore Ing. Filippeschi, Alessandro
Keywords
  • 3D body scanning
  • biometrics
  • computer vision
  • human body segmentation
  • RGBD camera
Graduation session start date
24/02/2022
Availability
Withheld
Release date
24/02/2092
Summary
Anthropometry plays an important role in a variety of fields such as product design, robotics, ergonomics, and medicine. For the latter, cardiac insufficiency is a widely spread disease, for which the human body limbs volume is a strong predictor. Their estimation is currently done by either tape measurements or body immersion. However, computer vision offers non-invasive, safe, cost-effective, and rapid methods capable of accurate body parameters evaluation.
In this work, a 3D body scanning apparatus is devised to estimate single body segment volume, thus overcoming the complexity of traditional evaluation while enhancing the accuracy of 3D body scanning. This system features a minimal setup consisting of two RGBD LiDAR cameras, acquiring a front and back depth image of a patient assuming a predetermined pose. A processing pipeline isolates and segments the body shape by the means of two DNNs, one for body landmark detection, the other for body segmentation. A common reference system provided by an ArUco marker before capture allows the unification of the two acquisitions into a single point cloud. The body shape is then reconstructed by fitting a template mesh to the unified point cloud with an ARAP deformation featuring a novel regularization term. The method has been experimentally assessed. A set of standardized anthropometric measurements is gathered on ten subjects and then compared to the measures extracted from the mesh after the scanning procedure.
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