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Now showing 1 - 5 of 5
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    Evolutionary Interactive Analysis of MRI Gastric Images Using a Multiobjective Cooperative-coevolution Scheme
    (The Eurographics Association, 2018) Al-Maliki, Shatha F.; Lutton, Évelyne; Boué, François; Vidal, Franck; {Tam, Gary K. L. and Vidal, Franck
    In this study, we combine computer vision and visualisation/data exploration to analyse magnetic resonance imaging (MRI) data and detect garden peas inside the stomach. It is a preliminary objective of a larger project that aims to understand the kinetics of gastric emptying. We propose to perform the image analysis task as a multi-objective optimisation. A set of 7 equally important objectives are proposed to characterise peas. We rely on a cooperation co-evolution algorithm called 'Fly Algorithm' implemented using NSGA-II. The Fly Algorithm is a specific case of the 'Parisian Approach' where the solution of an optimisation problem is represented as a set of individuals (e.g. the whole population) instead of a single individual (the best one) as in typical evolutionary algorithms (EAs). NSGA-II is a popular EA used to solve multi-objective optimisation problems. The output of the optimisation is a succession of datasets that progressively approximate the Pareto front, which needs to be understood and explored by the end-user. Using interactive Information Visualisation (InfoVis) and clustering techniques, peas are then semi-automatically segmented.
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    Towards a Survey of Interactive Visualization for Education
    (The Eurographics Association, 2018) Fırat, Elif E.; Laramee, Robert S.; {Tam, Gary K. L. and Vidal, Franck
    Graphic design and visualization are becoming fundamental components of education. The use of advanced visual design in pedagogy is growing and evolving rapidly. One of their aims is to enhance the educational process by facilitating better understanding of the subject with the use of graphical representation methods. Research papers in this field offer important opportunities to examine previously completed experiments and extract useful educational outcomes. This paper analyzes and classifies pedagogical visualization research papers to increase understanding in this area. To our knowledge, this is the first (work-in-progress) survey paper on advanced visualization for education. We categorize related research papers into original subject groups that enable researchers to compare related literature. Our novel classification enables researchers to find both mature and unexplored directions which can inform directions for future work. This paper serves as a valuable resource for both beginners and experienced researchers who are interested in interactive visualization for education.
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    Virtual Reality Callouts - Demonstrating Knowledge With Spatial-Related Textual Information
    (The Eurographics Association, 2019) Horst, Robin; Degreif, Anika; Mathy, Marvin; Dörner, Ralf; Vidal, Franck P. and Tam, Gary K. L. and Roberts, Jonathan C.
    Virtual (VR) and augmented reality (AR) can bring an added value during the demonstration of knowledge, as for example within an interactive research demo. Callouts are strings of text which are connected by a line to a specific feature of an object. These visual annotations can be used during such demos and can be placed in different kinds of media, such as illustrations, technical drawings, images and videos. Callouts are also used in virtual 3D environments to anchor textual information to a specific point in space. Therefore they can be a valuable tool for virtually demonstrating knowledge. The alignment of callouts in such information rich environments is an elemental factor within the view management of the VR scene. In this paper we propose a concept for interactive microlearning application for knowledge demonstration that uses callouts as a fundamental element. We distinguish three types of interactive callout-representations by their alignment relative to the user, for being static or dynamic in their position and orientation. Within an implementation of the different callout versions we show the feasibility and in a user study we indicate a user-preference towards static positioned callouts.
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    MolPathFinder: Interactive Multi-Dimensional Path Filtering of Molecular Dynamics Simulation Data
    (The Eurographics Association, 2016) Alharbi, Naif; Laramee, Robert S.; Chavent, Matthieu; Cagatay Turkay and Tao Ruan Wan
    Molecular Dynamics Simulations (MDS) play an important role in the field of computational biology. The simulations produce large high-dimensional, spatio-temporal data describing the motion of atoms and molecules. A central challenge in the field is the extraction and visualization of useful behavioral patterns from these simulations. Many visualization tools have been proposed to help computational biologists gain insight into MDS data. While recent developments focused on accelerating and optimising the rendering, it is still necessary to design new metaphors to better understand and filter MDS datasets. In this article, we are describing a set of tools to interactively filter and highlight dynamic and complex paths constituted by motions of molecules. In collaboration with computational biologists, we have tested our approach on large-scale, real data. Based on the user's feedback, our program helped scientists to navigate more easily through their dataset and isolate interesting patterns. Furthermore, our approach was useful to investigate both local and global behavior of molecular motions.
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    Robust and Flexible Puzzle Solving with Corner-based Cycle Consistent Correspondences
    (The Eurographics Association, 2019) Wang, T.; Vladimirov, K.; Goh, S.; Lai, Y.-K.; Xie, X.; Tam, G. K. L.; Vidal, Franck P. and Tam, Gary K. L. and Roberts, Jonathan C.
    Solving jigsaw puzzles is a classic problem in computer vision with various applications. Over the past decades, many useful approaches have been introduced. Most existing works use edge-wise similarity measures for assembling puzzles with square pieces of the same size, and recent work innovates to use the loop constraint to improve efficiency and accuracy. We observe that most existing techniques cannot be easily extended to puzzles with rectangular pieces of arbitrary sizes, and no existing loop constraints can be used to model such challenging scenarios. In this paper, we propose a new corner-wise matching approach, modelled using the MatchLift framework to solve square puzzles with cycle consistency. We further show one exciting example illustrating how puzzles with rectangular pieces of arbitrary sizes would be solved by our technique.