The objective of the course is to present the main technologies and methods for generating a digital 3D model acquiring a real scene. This possibility can be used in different applications in the Design field, for example digitalising a physical model that represents a “concept” developed manually; render a real digitalized object in a synthetic 3D scene and viceversa; produce the reverse modelling of an old industrial product to restyle it, etc. At the end of the course, students will be able to select the most suitable technology for the different project purposes, use it considering the inevitable size artefacts, and carry out the creation and post-production of a polygon model starting from a cloud of measured 3D points.

Students:
- applying knowledge and understanding: know the 3D modelling and reverse modelling software for creating digital prototypes;
- making judgements: can use the software studied, making suitable technological choices;
- communication skills: can build digital prototypes using 3D modelling and reverse modelling, useful for project representation and visualisation.

Theoretical introduction

General information on 3D measurement methods, with and without contact.

Nature of light.

Light-matter interaction.

Taxonomy of non-contact systems based on different forms of radiant energy.

Passive and active 3D sensing techniques.

Active 3D sensors

Active systems based on triangulation:

Laser scanner with single spot, single light plane, multiple light planes;

Full-field measurement based on fringe projection.

Active systems based on measurement of distances:

Time of Flight (TOF) measurement;

Phase Shift measurement on sinusoidally modulated light (PS);

Phase Shift on frequency-modulated light (FM-CW).

Principles of 3D metrology

Characterization of the errors of a range device.

Study of the possible artifacts generated by an active sensor.

Construction of polygonal models from acquired data

Topological concepts.

Working pipeline: draft project; acquisition, meshing; alignment; Iterative Closest Point (ICP) algorithm; merge; optimization; editing.

Passive 3D sensors.

Principles of photogrammetry.

Camera calibration.

Structure from motion, image matching, generation of dense 3D clouds.

Creating models from images.

Editing and re-texturing.

Standard software packages for achieving the entire Reverse Modeling process with active and passive techniques.

There are no pre-requisites for attendance.

The overall evaluation will be based on:

 1 multiple choice theoretical test, based on the contents illustrated in class and the bibliography texts (personal evaluation);

 1 exercise with active acquisition techniques (group assessment);

 1 exercise with passive acquisition techniques (group assessment);

 a critical presentation of the work carried out at the end of the course.

2020-21 Course update