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Now showing 1 - 5 of 5
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    View Dependent Decompression for Web-based Massive Triangle Meshes Visualisation
    (The Eurographics Association, 2022) Cecchin, Alice; Du, Paul; Pastor, Mickaël; Agouzoul, Asma; Sauvage, Basile; Hasic-Telalovic, Jasminka
    We introduce a framework extending an existing progressive compression-decompression algorithm for 3D triangular meshes. First, a mesh is partitioned. Each resulting part is compressed, then joined with one of its neighbours. These steps are repeated following a binary tree of operations, until a single compressed mesh remains. Decompressing the mesh involves progressively performing those steps in reverse, per node, and locally, by selecting the branch of the tree to explore. This method creates a compact and lossless representation of the model that allows its progressive and local reconstruction. Previously unprocessable meshes can be visualized on the web and mobile devices using this technique.
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    Automatic Hierarchical Arrangement of Vector Designs
    (The Eurographics Association, 2021) Fisher, Matthew; Agarwal, Vineet; Beri, Tarun; Theisel, Holger and Wimmer, Michael
    We present a method that transforms an unstructured vector design into a logical hierarchy of groups of objects. Each group is a meaningful collection, formed by proximity in visual characteristics (like size, shape, color, etc.) and spatial location of objects and models the grouping principles designers use. We first simplify the input design by partially or completely flattening it and isolate duplicate geometries in the design (for example, repeating patterns due to copy and paste operations). Next we build the object containment hierarchy by assigning objects that are wholly enclosed inside the geometry of other objects as children of the enclosing parent. In the final clustering phase, we use agglomerative clustering to obtain a bottom-up hierarchical grouping of all objects by comparing and ranking all pairs of objects according to visual and spatial characteristics. Spatial proximity segregates far apart objects, but when they are identical (or near identical) designers generally prefer to keep (and edit) them together. To accommodate this, we detect near identical objects and group them together during clustering despite their spatial separation. We further restrict group formation so that z-order disturbances in the design keep the visual appearance unaffected for tightly-overlapping geometry. The generated organization is equivalent to the original design and the organization results are used to facilitate abstract navigation (hierarchical, lateral or near similar) and selections in the design. Our technique works well with a variety of input designs with commonly identifiable objects and structural patterns.
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    Project in Visualization and Data Analysis: Experiences in Designing and Coordinating the Course
    (The Eurographics Association, 2021) Kucher, Kostiantyn; Martins, Rafael M.; Kerren, Andreas; Sousa Santos, Beatriz and Domik, Gitta
    Visual analytics involves both visual and computational components for empowering human analysts who face the challenges of making sense and making use of large and heterogeneous data sets in various application domains. In order to facilitate the learning process for the students at higher education institutions with regard to both the theoretical knowledge and practical skills in visual analytics, the respective courses must cover a variety of topics and include multiple assessment methods and activities. In this paper, we report on the design and first instantiation of a full term project-based course in visualization and data analysis, which was recently offered to graduate and post-graduate students at our department and met with positive feedback from the course participants.
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    Teaching Data-driven Video Processing via Crowdsourced Data Collection
    (The Eurographics Association, 2021) Reimann, Max; Wegen, Ole; Pasewaldt, Sebastian; Semmo, Amir; Döllner, Jürgen; Trapp, Matthias; Sousa Santos, Beatriz and Domik, Gitta
    This paper presents the concept and experience of teaching an undergraduate course on data-driven image and video processing. When designing visual effects that make use of Machine Learning (ML) models for image-based analysis or processing, the availability of training data typically represents a key limitation when it comes to feasibility and effect quality. The goal of our course is to enable students to implement new kinds of visual effects by acquiring training datasets via crowdsourcing that are used to train ML models as part of a video processing pipeline. First, we propose our course structure and best practices that are involved with crowdsourced data acquisitions. We then discuss the key insights we gathered from an exceptional undergraduate seminar project that tackles the challenging domain of video annotation and learning. In particular, we focus on how to practically develop annotation tools and collect high-quality datasets using Amazon Mechanical Turk (MTurk) in the budget- and time-constrained classroom environment. We observe that implementing the full acquisition and learning pipeline is entirely feasible for a seminar project, imparts hands-on problem solving skills, and promotes undergraduate research.
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    Conveying Firsthand Experience: The Circuit Parcours Technique for Efficient and Engaging Teaching in Courses about Virtual Reality and Augmented Reality
    (The Eurographics Association, 2021) Dörner, Ralf; Horst, Robin; Sousa Santos, Beatriz and Domik, Gitta
    Providing the opportunity for hands-on experience is crucial when teaching courses about Virtual Reality (VR) and Augmented Reality (AR). However, the workload on the educator's side for providing these opportunities might be prohibitive. In addition, other organizational challenges can arise, for example, demonstrations of VR/AR application in a course might be too time-consuming, especially if the course is attended by many students. We present the Circuit Parcours Technique to meet these challenges. Here, in a well-organized event, stations with VR/AR demonstrations are provided in parallel, and students are enlisted to prepare and conduct the demonstrations. The event is embedded in a four-phase model. In this education paper, the technique is precisely described, examples for its flexible usage in different teaching situations are provided, advantages such as time efficiency are discussed, and lessons learned are shared from our experience with using this method for more than 10 years. Moreover, learning goals are identified that can be achieved with this technique besides gaining personal experience.