Technical Papers

Materials and Images

Thursday, 29 November 16:15 - 18:15 |  Peridot 206

 Material Memex: Automatic Material Suggestions for 3D Objects - Picture

Material Memex: Automatic Material Suggestions for 3D Objects

Material found on 3D objects and their parts correlates with the geometric shape of the parts and their relation to other parts of the same object. This work proposes to model this context-dependent correlation by learning it from a database containing several hundreds of objects and their materials.


Arjun Jain, Max-Planck-Institut für Informatik
Hans-Peter Seidel, Max-Planck-Institut für Informatik
Thorsten Thormeahlen, Max-Planck-Institut für Informatik
Tobias Ritschel, Max-Planck-Institut für Informatik


Interactive Bi-scale Editing of Highly Glossy Materials - Picture

Interactive Bi-scale Editing of Highly Glossy Materials

We present a new technique for bi-scale material editing using
Spherical Gaussians.


Kei Iwasaki, Wakayama University
Yoshinori Dobashi, Hokkaido University
Tomoyuki Nishita, The University of Tokyo


An Inverse Problem Approach for Automatically Adjusting the Parameters for Rendering Clouds Using Photographs - Picture

An Inverse Problem Approach for Automatically Adjusting the Parameters for Rendering Clouds Using Photographs

Parameters for rendering synthetic clouds realistically are estimated automatically from photographs. Genetic algorithms are used to search for optimal parameters. Once the parameters have been obtained, the user can render the synthetic clouds with various viewpoints, sunlight directions, and sunlight colors.


Yoshinori Dobashi, Hokkaido University, JST CREST
Wataru Iwasaki, Hokkaido University
Ayumi Ono, Hokkaido University
Tsuyoshi Yamamoto, Hokkaido University
Yonghao Yue, The University of Tokyo
Tomoyuki Nishita, The University of Tokyo


Lighting Hair From The Inside: A Thermal Approach To Hair Reconstruction - Picture

Lighting Hair From The Inside: A Thermal Approach To Hair Reconstruction

We present a novel technique to reconstruct hairstyles based on images taken with a thermal camera, avoiding thus several issues related to conventional image-based approaches.


Tomás Lay Herrera, Institut für Informatik II, Universität Bonn
Arno Zinke, TeamUp Technologies, Bonn
Andreas Weber, Institut für Informatik II, Universität Bonn


New Measurements Reveal Weaknesses of Image Quality Metrics in Evaluating Graphics Artifacts - Picture

New Measurements Reveal Weaknesses of Image Quality Metrics in Evaluating Graphics Artifacts

We propose rendering-oriented datasets for image quality evaluation, which provide detailed distortion maps along with the probability of their detection by human observers. For existing full-reference image quality metrics our datasets turned out to be very demanding, and our analysis of metric failures suggests directions for improvement.


Martin Cadik, Max-Planck-Institut für Informatik
Robert Herzog, Max-Planck-Institut für Informatik
Rafał Mantiuk, Bangor University
Karol Myszkowski, Max-Planck-Institut für Informatik
Hans-Peter Seidel, Max-Planck-Institut für Informatik