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44: Image-Based Modeling
Tuesday, Half Day
1:30 – 5:15 pm
Room 006AB
As the complexity of image-based models grows, researchers
are facing increasing challenges associated with collecting
and processing massive amounts of radiance data. This
course is an overview of new technologies for collecting
and analyzing densely sampled radiance data and building
image-based models that are compact, accurate, and easy
to render.
Prerequisites
Basic knowledge of rendering and illumination, including
reflectance models, shading, and texture mapping. Some
knowledge of 3D modeling from images is helpful but not
required.
Organizer
Radek Grzeszczuk
Intel Corporation
Lecturers
Jean-Yves Bouguet
Radek Grzeszczuk
Intel Corporation
Leonard McMillan
Massachusetts Institute of Technology
Ko Nishino
University of Tokyo
Hanspeter Pfister
Mitsubishi Electric Research Lab
Marc Pollefeys
Katholieke Universiteit Leuven
Schedule
| 1:30 |
Introduction
Grzeszczuk
Re-Rendering From a Dense/Sparse Set of Images
Nishino |
| 2:15 |
Acquisition
of Surface Light Fields
Bouguet |
| 2:45 |
Hardware-Accelerated
Rendering of Surface Light Fields
Grzeszczuk |
| 3:15 |
Break |
| 3:30 |
Acquisition
of Light Field Data using Hand-Held Camera
Pollefeys |
| 4:15 |
Image-Based
3D Photography using Opacity Hulls (Part I)
McMillan |
4:45 |
Image-Based
3D Photography Using Opacity Hulls (Part II)
Pfister |
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