EG 2023 - Tutorials

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Browsing EG 2023 - Tutorials by Title

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    Effective User Studies in Computer Graphics
    (The Eurographics Association, 2023) Malpica, Sandra; Sun, Qi; Kellnhofer, Petr; Beacco, Alejandro; Senel, Gizem; McDonnell, Rachel; Flores Vargas, Mauricio; Serrano, Ana; Slusallek, Philipp
    User studies are a useful tool for researchers, allowing them to collect data on how users perceive, interact with and process different types of sensory information. If planned in advance, user experiments can be leveraged in every stage of a research project, from early design, prototyping and feature exploration to applied proofs of concept, passing through validation and data collection for model training. User studies can provide the researcher with different types of information depending on the chosen methodology: user performance metrics, surveys and interviews, field studies, physiological data, etc. Considering human perception and other cognitive processes is particularly important in computer graphics, where most research produces outputs whose ultimate purpose is to be seen or perceived by a human. Being able to measure in an objective and systematic way how the information we generate is integrated into the representational space humans create to situate themselves in the world means that researchers will have more information to implement optimal algorithms, tools and techniques. In this tutorial we will give an overview of good practices for user studies in computer graphics with a particular focus on virtual reality use cases. We will cover the basics on how to design, carry out and analyze good user studies, as well as different particularities to be taken into account in immersive environments.
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    EUROGRAPHICS 2023: Tutorials Frontmatter
    (Eurographics Association, 2023) Serrano, Ana; Slusallek, Philipp; Serrano, Ana; Slusallek, Philipp
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    Learning with Music Signals: Technology Meets Education
    (The Eurographics Association, 2023) Müller, Meinard; Serrano, Ana; Slusallek, Philipp
    Music information retrieval (MIR) is an exciting and challenging research area that aims to develop techniques and tools for organizing, analyzing, retrieving, and presenting music-related data. Being at the intersection of engineering and humanities, MIR relates to different research disciplines, including signal processing, machine learning, information retrieval, musicology, and the digital humanities. In this tutorial, using music as a tangible and concrete application domain, we will approach the concept of learning from different angles, addressing technological and educational aspects. When talking about learning in an engineering context, one immediately thinks of data-driven techniques such as deep learning (DL), where computer-based systems are trained to extract complex features and hidden relationships from given examples. In this tutorial, we will introduce various music analysis and retrieval tasks, where we start with classical engineering approaches. We then show how such approaches may be rephrased or simulated by DL-based systems, thus indicating new avenues toward building more explainable and hybrid machine-learning systems by learning from the experience of traditional engineering approaches and integrating knowledge from the music domain. Beyond this technical perspective, another aim of this tutorial is to approach the concept of learning from an educational perspective. We argue that music, being an essential part of our lives that everyone feels connected to, yields an intuitive entry point to support education in technical disciplines. In this tutorial, we will show how music may serve as a vehicle to make learning in signal processing and machine learning an interactive pursuit. In this context, we will also introduce a novel collection of educational material for teaching and learning fundamentals of music processing (FMP). This collection, referred to as FMP notebooks (https://www.audiolabs-erlangen.de/FMP) can be used to study both theory and practice, generate educational material for lectures, and provide baseline implementations for many MIR tasks. The tutorial's novelty lies in how it presents a holistic approach to learning using music as a challenging and tangible application domain. In this way, the tutorial serves several purposes: it gives a gentle introduction to MIR while introducing a new software package for teaching and learning music processing, it highlights avenues for developing explainable machine-learning models, and it discusses how recent technology can be applied and communicated in interdisciplinary research and education.
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    Modern High Dynamic Range Imaging at the Time of Deep Learning
    (The Eurographics Association, 2023) Banterle, Francesco; Artusi, Alessandro; Serrano, Ana; Slusallek, Philipp
    In this tutorial, we introduce how the High Dynamic Range (HDR) imaging field has evolved in this new era where machine learning approaches have become dominant. The main reason of this success is that the use of machine learning and deep learning have automatized many tedious tasks achieving high-quality results overperforming classic methods. After an introduction on classic HDR imaging and its open problem, we will summarize the main approaches for: merging of multiple exposures, single image reconstructions or inverse tone mapping, tone mapping, and display visualization. Finally, we will highlights the still open problems in this machine learning era, and possible direction on how to solve them.
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    Using Vulkan for Graphics Research
    (The Eurographics Association, 2023) Castorina, Marco; Sassone, Gabriel; Serrano, Ana; Slusallek, Philipp
    The Vulkan API has has been released in 2016 and it has continued to evolve to include the latest hardware capabilities. Compared to OpenGL, it is a more verbose API that requires a deeper knowledge of the underlying hardware architecture. While this can make the API more difficult to get started with, it also rewards developers with finer grained control over resource management, multi-threading and work submission. This flexibility allows developers to achieve better performance over older APIs and opens the door to novel techniques that would have been harder, if not impossible, to implement before. In this tutorial we are going to provide an introduction to the core Vulkan API concepts and how they map to the underlying hardware. We are going to demonstrate how to leverage async compute to overlap graphics and compute work for better performance. We will provide detailed examples that make use of cutting-edge features like Mesh Shaders and Ray Tracing to achieve state of the art results in real-time rendering.