EG2022

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https://diglib.eg.org/handle/10.2312/2633163

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Browsing EG2022 by Subject "Applied computing"

Now showing 1 - 4 of 4
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    Introduction to Computer Graphics: A Visual Interactive Approach
    (The Eurographics Association, 2022) Loscos, Celine; Bourdin, Jean-Jacques; Paquette, Eric
    Computer graphics is a difficult topic, requiring associating mathematics and programming skills. When initially taught at undergraduate levels, there are several factors which discourage students. First, programming a first computer graphics program requires a substantial initial framework which can be intimidating for many of them. Second, understanding and applying mathematical concepts is very often overwhelming. To counter this intimidating feeling, a new teaching approach was proposed in 2018 to 3rd year undergraduate computer science students. The course was split into two parts, theory and practice. The theoretical concepts were seen in class, with course handouts and table exercises resembling closely to traditional computer graphics learning. The originality of the course comes from a new way of practicing 3D programming. Practical labs were built upon the Unity game engine programming platform, adapted to match the theoretical concepts seen in classroom. Conclusions are drawn over 4 years of teaching this course. When taught using an accompanying easy-to-access graphics programming platform, computer graphics becomes a more attractive course for students with lower mathematics and programming skills. It is also very satisfactory for skillful students as it enables them to grab and master concepts quickly to reach interesting final lab achievements.
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    Multimodal Early Raw Data Fusion for Environment Sensing in Automotive Applications
    (The Eurographics Association, 2022) Pederiva, Marcelo Eduardo; Martino, José Mario De; Zimmer, Alessandro; Sauvage, Basile; Hasic-Telalovic, Jasminka
    Autonomous Vehicles became every day closer to becoming a reality in ground transportation. Computational advancement has enabled powerful methods to process large amounts of data required to drive on streets safely. The fusion of multiple sensors presented in the vehicle allows building accurate world models to improve autonomous vehicles' navigation. Among the current techniques, the fusion of LIDAR, RADAR, and Camera data by Neural Networks has shown significant improvement in object detection and geometry and dynamic behavior estimation. Main methods propose using parallel networks to fuse the sensors' measurement, increasing complexity and demand for computational resources. The fusion of the data using a single neural network is still an open question and the project's main focus. The aim is to develop a single neural network architecture to fuse the three types of sensors and evaluate and compare the resulting approach with multi-neural network proposals.
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    Procedural Bridges-and-pillars Support Generation
    (The Eurographics Association, 2022) Freire, Marco; Hornus, Samuel; Perchy, Salim; Lefebvre, Sylvain; Pelechano, Nuria; Vanderhaeghe, David
    Additive manufacturing requires support structures to fabricate parts with overhangs. In this paper, we revisit a known support structure based on bridges-and-pillars (see Figure 1). The support structures are made of vertical pillars supporting horizontal bridges. Their scaffolding structure makes them stable and reliable to print. However, the algorithm heuristic search does not scale well and is prone to produce contacts with the parts, leaving scars after removal. We propose a novel algorithm for this type of supports, focusing on avoiding unnecessary contacts with the part as much as possible. Our approach builds upon example-based model synthesis to enable early detection of collision-free passages as well as non-reachable regions.
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    RePiX VR - Learning environment for the Rendering Pipeline in Virtual Reality
    (The Eurographics Association, 2022) Heinemann, Birte; Görzen, Sergej; Schroeder, Ulrik; Bourdin, Jean-Jacques; Paquette, Eric
    Virtual reality can be used to support computer graphics teaching, e.g. by offering the chance to illustrate 3D processes that are difficult to convey. This paper describes the development and first evaluations of RePiX VR a virtual reality tool for computer graphics education, which focuses on the teaching of fundamental concepts of the rendering pipeline and offers researchers the opportunity to study learning in VR by integrating learning analytics. For this, the tool itself is presented and the evaluation, which uses quantitative methods and learning analytics to show the effectiveness of the tool. The first evaluations show that even learners without prior knowledge can use the VR tool and learn the first basics of computer graphics.