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Course unit
COMPUTER VISION AND 3D GRAPHICS
INO2043950, A.A. 2013/14

Information on the course unit
Degree course Second cycle degree in
TELECOMMUNICATION ENGINEERING
IN0524, Regulation 2008/09, A.Y. 2013/14
1090754
Number of ECTS credits allocated 6.0
Course unit English denomination COMPUTER VISION AND 3D GRAPHICS
Department of reference Department of Information Engineering
Mandatory attendance No
Language of instruction English
Campus PADOVA

Lecturers
Teacher in charge GUIDO MARIA CORTELAZZO ING-INF/03

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses ING-INF/03 Telecommunications 6.0

Mode of delivery (when and how)
Period Second semester
Year 2nd Year
Teaching methods frontal

Organisation of didactics
Type of hours Credits Hours of
teaching
Hours Individual
study
Shifts
Lecture 6.0 48 102.0 No turn

Calendar
Start of activities 03/03/2014
End of activities 14/06/2014

Examination board
Board From To Members of the board
3 A.A. 2016/2017 01/10/2016 15/03/2018 MILANI SIMONE (Presidente)
ZANUTTIGH PIETRO (Membro Effettivo)
BENVENUTO NEVIO (Supplente)
CALVAGNO GIANCARLO (Supplente)
CORVAJA ROBERTO (Supplente)
ERSEGHE TOMASO (Supplente)
LAURENTI NICOLA (Supplente)
PUPOLIN SILVANO (Supplente)
ROSSI MAURA (Supplente)
TOMASIN STEFANO (Supplente)
VANGELISTA LORENZO (Supplente)
ZANELLA ANDREA (Supplente)
ZORZI MICHELE (Supplente)
01/10/2013 15/03/2015 CORTELAZZO GUIDO MARIA (Presidente)
ZANUTTIGH PIETRO (Membro Effettivo)
CALVAGNO GIANCARLO (Supplente)

Syllabus
Prerequisites: The Digital Signal Processing and Image and Video Analysis class are recommended although not strictly necessary
Target skills and knowledge: The course offers a guided tour of the computer vision and computer graphics topics needed for current virtual and augmented reality applications.
The course rationale is the introduction of the notions and techniques to go
a) from 3D scenes to images by way of real imaging systems;
b) from images to 3D scene models;
c) and from 3D models to images by way of virtual cameras.
Part a) has the objective of explaining the operation and the mathematical models of current imaging systems (e.g., video-cameras, Time of Flight systems, kinect) in the language of computational photography. The objective of Part b) is the coverage of two topics: 3D recontruction from images (with special focus on stereo and active stereo systems) and the 3D modeling pipeline (i.e., the procedures to obtain full 3D models from depth maps). The objective of Part (c) is to introduce the rendering methods as approximate solution of the rendering equation.

The course is structured in order to give the students a clear sense for the deep interconnections between the notions of computer vision and computer graphics encountered in virtual and augmented reality applications, interconnections due to the fact that that 3D reconstruction (computer vision) can be interpreted as the inverse problem of rendering (computer graphics).

Within its time limits, the course also aims to introduce the students to current computer vision and computer graphics tools such as OpenCV, Point CloudLibrary and OpenGL.
Examination methods: Written test
Assessment criteria: The Computer Vision and 3DGraphics class covers a wide range of topics mainly across Computer Vision and Computer Graphics since a wide panorama is a good asset to face the fast evolution of these fields.
Nevertheless the student evaluation will be focused on the concepts necessary for building and visualizing 3d models within typical augmented and virtual reality contexts.
Such topics will be clearly indicated during the course and in the course material.
Every efforts on the student part revealing personal involvement and special care will be recognized in terms of scores.
Course unit contents: a) From 3D scene to images via real imaging systems

1 Image formation and camera model

Perspective projection
Pin-hole camera
Thin lenses
Simplified camera model
General camera model and its properties
Digital images

2 Camera calibration

DLT method
Parameters extraction
Plane-induced homography
Computation of the homography (DLT)
Planar Calibration
Radial Distortion

b) From images to 3D scene model (or 3D reconstruction in Computer Vision)

3 Stereopsys: geometry

3D Triangulation
Linear-eigen method
Epipolar geometry
Epipolar Rectification
Essential matrix, factorizzation and computation
Motion and structure from calibrated homography

4 Salient points extraction

Harris e Stephens method
Salient points correspondence
KLT algorithm
Scale Invariant Feature Transform (SIFT)

5 Stereopsys: Corrispondence

Local correspondence methods
Window correspondence methods
Accuracy-reliability trade-off Indicatori di affidabilita’
Occlusions
Other local methods
Global correspondence methods
Correspondence space


6 Mosaics and image synthesis

Mosaics:
Allignement
Geometric trasformation
Blending
Other applications
Image stabilization
Orthogonal rectification
Image Synthesis
Depth transfer
Disparity interpolation
Epipolar trasfer

7 Non-calibrated reconstruction

Fundamental matrix and its computation
Projective reconstruction from 2 and N views
Self-calibration
Euclidean upgrade
Methd of Mendonca e Cipolla
Tomasi-Kanade factorization
Sequential approach:
Correspondence validation
Incremental reconstruction
Bundle adjustement

8 Optical flow

Motion field: computation of motion and structure
Optical flow: Lucas-Kanade method

9 3D Modeling Pipeline

Quaternions
Absolute orientation by Horn and Arun methods
Rotation interpolation by SLERP method
Iterated Closest Point (ICP)
Global Registration: Lu & Milios method
Surface integration: non-volumetric (Turk & Levoy method) and volumetric methods (Wheeler, Ikehuchi & Sato method)
Mesh semplification


c) From scene 3D models to images by way of virtual 3D video-cameras (Computer Graphics)

10 Rendering

Rendering: geometry
Proiective projection convention in graphics
Ray Casting
Rendering: radiometry
Fundamental quantities
BRDF and fundamental BRDF models (Lambertian, specular, glossy)
Lambertian surfaces: Relationship between radiosity and irradiance
The radiance (or rendering) equation and its solution

11 Illumination models

The radiance solution by local metohds: Phong and ModelloCook-Torrance models
Light types
The radiance solution by grobal metohds
Ray tracing: Whitted method
Radiosity: radiosity equation in continuous and discrete form


12 Rasterization

Geometric trasformations
Clipping
Hidden surface removal
Scan conversion
Shading: Flat, Phong e Gouraud methods
The OpenGL pipeline
“Multi-pass” techniques

13 Mapping methods

Texture mapping in 1 e 2 passes
Foreword and backword mapping.
Aliasing: minification and maxification.
Bump mapping

14 Fotorealism

Reflection map
Light map
Geometric shading
Trasparency
Planned learning activities and teaching methods: The course offers a guided tour of the computer vision and computer graphics topics needed for current virtual and augmented reality applications. The visited and learned topics are:

• Image formation: mathematical models of cameras and Time of Flight systems.
• Camera calibration: procedures for metrical measurements from images
• Computational stereopsis: 3D scene structure derived from 2 or more images obtained from calibrated cameras
• Structure from motion: 3D scene structure derived from 1 or more calibrated moving cameras
• Un-calibrated 3D reconstruction: 3D scene structure derived from un-calibrated cameras.
• 3D registration: pairwise and global registration (or SLAM) of depth-maps into a point cloud
• 3D data integration and geometrical simplification: integration of overlapping point clouds into tessellated surfaces and their simplification
• Rendering methods: ray casting, ray tracing, radiosity and rasterization

The topics are treated by means of frontal lectures with computational examples based on MATLAL, Open CV and Open GL.
The appraisal is stimulated by homeworks confronting the student with practical situations due to the concepts seen in class.
Additional notes about suggested reading: The course purposely hybridates two disciplines, computer vision and computer topics, in order to focus on 3D model construction and visualization and there is no textbook on such a specific topic.
The study material is given by the class-notes made available before every class meeting.
The notes distill and condense various research papers and content coming from several textbooks, among which:
Richard Szeliski, "Computer Vision: Algorithms and Applications", Springer, New York, 2010
A. Fusiello, "Visione Computazionale", F. Angeli, Milano, 2013
James D. Foley, Andries van Dam, Steven K. Feiner, John F. Hughes, "Computer Graphics: Principles and Practice in C" (2nd Edition), Addison-Wesley, New York, 2000
Textbooks (and optional supplementary readings)
  • Richard Szeliski, Computer Vision: Algorithms and Applications. New York: Springer, 2010. Only a reference but not the text-book Cerca nel catalogo
  • James D. Foley, Andries van Dam, Steven K. Feiner, John F. Hughes, Computer Graphics: Principles and Practice in C. New York: Addison-Wesley, 2000. Only a reference but not the text-book Cerca nel catalogo
  • A. Fusiello, Visione Computazionale. Milano: Franco Angeli, 2013. Only a reference but not the text-book Cerca nel catalogo