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Semester (Sem)
1First Semester
2Second Semester
AAnnual course
Educational activities
BIdentifying activities
Course completely offered in italian
Course completely offered in english
--Not available
Innovative teaching
The credits shown next to this symbol indicate the part of the course CFUs provided with Innovative teaching.
These CFUs include:
  • Subject taught jointly with companies or organizations
  • Blended Learning & Flipped Classroom
  • Massive Open Online Courses (MOOC)
  • Soft Skills
Course Details
Academic Year 2017/2018
School School of Industrial and Information Engineering
Name (Master of Science degree)(ord. 270) - BV (483) Mechanical Engineering
Track ME5 - Advanced Mechanical Design
Programme Year 2

Course Details
ID Code 097454
Course Type Mono-Disciplinary Course
Credits (CFU / ECTS) 6.0
Semester Second Semester
Course Description Brief description of the subjects Starting from an overview on the human vision modeling, the course shows the relationship between an ideal perspec-tive image and the corresponding three-dimensional scene. The characteristics of a real image-capturing device, such as a digital photo camera, are then highlighted, analyzing how the different optical and electronic components tend to change the acquired image with respect to the ideal one, and how such changes can be mathematically modeled through a calibration process. Starting from calibrated images, techniques for relative orientation, intersection and scaling according to some metric references on the scene are then shown. The course, then, introduces the functioning principles of the different active range sensors currently available on the market, categorizing them in a general framework and specifying accordingly their metrological characteristics. The course provides a set of rules for properly employing this kind of equipment in the 3D digitization of an object surface, in order to reliably generate a cloud of 3D points representing its spatial sampling. The course gives also the skills needed for planning a 3D acquisition project with a set of range maps taken from different orientations, keeping into account possible artifacts due to different light-to-material interactions produced by wrong orientations between the 3D sensor and the surface to be imaged. The course shows also the 3D pipeline for digitally manipulating the raw 3D data up to the final mesh model through registration, merge and mesh editing. In order to effectively provide these skills, the course foresees the execution of an exercise for capturing geometric elements on a real 3D scene starting from 2D images (passive devices). Groups of students will be asked to produce a substantial amount of practical work both in a 3D lab and on computers in order to post-processing their own images with specific software packages. Afterwards, the course involves the students in an analogous 3D capturing exercise of a real object with active devices, where groups of students will work both in a 3D lab and on computers for the post-processing of the acquired 3D data. The technologies shown as theoretical units in the first part of the course are therefore experimented in practical applications so as to allow the students to directly interact with the whole Reverse Engineering process based on both passive 3D acquisition with Computer Vision techniques, active 3D acquisition, 3D processing, 3D model generation and presentation. Synthesis of the subjects Theoretical introduction. Coordinate systems and related operations. 3D data extraction from ideal 2D images. Real image capturing systems. 3D data extraction from real 2D images (passive 3D). Active 3D imaging systems based on angular measurements. Active 3D imaging systems based on measurement of distances. Integration of complementary 3D capture methods. Principles of 3D metrology. 3D model generation through Computer Vision. 3D model generation through active range imaging. Overview of industrial applications. Workshop for groups of 2-3 students.
Scientific-Disciplinary Sector (SSD)
Educational activities SSD Code SSD Description CFU

Schedule, add and removeAlphabetical groupLecturer(s)LanguageTeaching Assignment Details
From (included)To (excluded)
---AZZZZMicoli Laura Loredana
manifesti v. 3.7.1 / 3.7.1
Area Servizi ICT