EG 2020 - Tutorials
https://diglib.eg.org:443/handle/10.2312/2632889
2024-03-28T12:48:06ZFrom Perception to Interaction with Virtual Characters
https://diglib.eg.org:443/handle/10.2312/egt20201001
From Perception to Interaction with Virtual Characters
Zell, Eduard; Zibrek, Katja; Pan, Xueni; Gillies, Marco; McDonnell, Rachel
Fjeld, Morten and Frisvad, Jeppe Revall
This course will introduce students, researchers and digital artists to the recent results in perceptual research on virtual characters. It covers how technical and artistic aspects that constitute the appearance of a virtual character influence human perception, and how to create a plausibility illusion in interactive scenarios with virtual characters. We will report results of studies that addressed the influence of low-level cues like facial proportions, shading or level of detail and higher-level cues such as behavior or artistic stylization. We will place emphasis on aspects that are encountered during character development, animation, interaction design and achieving consistency between the visuals and storytelling. We will close with the relationship between verbal and non-verbal interaction and introduce some concepts which are important for creating convincing character behavior in virtual reality. The insights that we present in this course will serve as an additional toolset to anticipate the effect of certain design decisions and to create more convincing characters, especially in the case where budgets or time are limited.
2020-01-01T00:00:00ZEUROGRAPHICS 2020: Tutorials Frontmatter
https://diglib.eg.org:443/handle/10.2312/egt20202000
EUROGRAPHICS 2020: Tutorials Frontmatter
Fjeld, Morten; Frisvad, Jeppe Revall
Fjeld, Morten and Frisvad, Jeppe Revall
2020-01-01T00:00:00ZBlack Box Geometric Computing with Python: From Theory to Practice
https://diglib.eg.org:443/handle/10.2312/egt20201000
Black Box Geometric Computing with Python: From Theory to Practice
Koch, Sebastian; Schneider, Teseo; Li, Chengchen; Panozzo, Daniele
Fjeld, Morten and Frisvad, Jeppe Revall
The first part of the course is theoretical, and introduces the finite element method trough interactive Jupyter notebooks. It also covers recent advancements toward an integrated pipeline, considering meshing and element design as a single challenge, leading to a black box pipeline that can solve simulations on ten thousand in the wild meshes, without any parameter tuning. In the second part we will move to practice, introducing a set of easy-to-use Python packages for applications in geometric computing. The presentation will have the form of live coding in a Jupyter notebook. We have designed the presented libraries to have a shallow learning curve, while also enabling programmers to easily accomplish a wide variety of complex tasks. Furthermore, these libraries utilize NumPy arrays as a common interface, making them highly composable with each-other as well as existing scientific computing packages. Finally, our libraries are blazing fast, doing most of the heavy computations in C++ with a minimal constant-overhead interface to Python. In the course, we will present a set of real-world examples from geometry processing, physical simulation, and geometric deep learning. Each example is prototypical of a common task in research or industry and is implemented in a few lines of code. By the end of the course, attendees will have exposure to a swiss-army-knife of simple, composable, and high-performance tools for geometric computing.
2020-01-01T00:00:00Z