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Now showing 1 - 10 of 66
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    CEIG 2024: Frontmatter
    (The Eurographics Association, 2024) Marco, Julio; Patow, Gustavo; Marco, Julio; Patow, Gustavo
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    Enhancing Medical Diagnosis and Treatment Planning through Automated Acquisition and Classification of Bone Fracture Patterns
    (The Eurographics Association, 2024) Pérez-Cano, Francisco Daniel; Parra-Cabrera, Gema; Camacho-García, Rubén; Jiménez, Juan José; Marco, Julio; Patow, Gustavo
    The extraction of the main features of a fractured bone area enables subsequent virtual reproduction for bone simulations. Exploring the fracture zone for other applications remains largely unexplored in current research. Recreating and analyzing fracture patterns has direct applications in medical training programs for traumatologists, automatic bone fracture reduction algorithms, and diagnostics. Furthermore, pattern classification aids in establishing treatment guidelines that specialists can follow during the surgical process. This paper focuses on the process of obtaining an accurate representation of bone fractures, starting with computed tomography scans, and subsequently classifying these patterns using a convolutional neural network. The proposed methodology aims to streamline the extraction and classification of fractures from clinical cases, contributing to enhanced diagnosis and medical simulation applications.
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    User-reconfigurable CAD Feature Recognition in 1- and 2-topologies with Reduction of Search Space via Geometry Filters
    (The Eurographics Association, 2019) Corcho, Juan Camilo Pareja; Acosta, Oscar Mauricio Betancur; Ruiz, Oscar E.; Cadavid, Carlos; Casas, Dan and Jarabo, Adrián
    In the context of Computer-Aided Design and Manufacturing, the problem of feature recognition plays a key role in the integration of systems. Until now, compromises have been reached by only using FACE-based geometric information of prismatic CAD models to prune the search domain. This manuscripts presents a feature recognition method which more aggressively prunes the search space with reconfigurable geometric tests. This reconfigurable approach allows to enforce arbitrary confluent tests which are topologic and geometric, with enlarged domain. The test sequence is itself a graph (i.e. not a linear or total-order sequence). Unlike the existing methods which are FACE-based, the present one permits combinations of topologies whose dimensions are 2, 1 or 0. This system has been implemented in an industrial environment. The industrial incarnation allows industry-based customization and is faster when compared to topology-based feature recognition. Future work is required in improving robustness of search conditions and improving the graphic input interface.
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    Simulation of Mechanical Weathering for Modeling Rocky Terrains
    (The Eurographics Association, 2024) Mateos, Diego; Carranza, Luis; Susin, Anton; Argudo, Oscar; Marco, Julio; Patow, Gustavo
    Synthetic terrains play a vital role in various applications, including entertainment, training, and simulation. This work focuses on rocky terrains akin to those found in alpine environments, which contain many complex features such as sharp ridges, loose blocks, or overhangs that are often inadequately represented by standard 2D elevation maps. We propose a novel method based on a simplified simulation of mechanical erosion processes commonly observed in high-altitude terrains, in particular the weathering due to freeze-thaw cycles. The ultimate objective is to generate plausible rocky geometry from existing 3D models, as well as account for the temporal evolution due to these weathering processes. Additionally, we have developed an artist-friendly tool integrated as an add-on into Blender.
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    Cylindrical Transform Slicing of Revolute Parts with Overhangs for Laser Metal Deposition
    (The Eurographics Association, 2022) Montoya-Zapata, Diego; Moreno, Aitor; Ortiz, Igor; Ruiz-Salguero, Oscar; Posada, Jorge; Posada, Jorge; Serrano, Ana
    In the context of Laser Metal Deposition (LMD), temporary support structures are needed to manufacture overhanging features. In order to limit the need for supports, multi-axis machines intervene in the deposition by sequentially repositioning the part. Under multi-axis rotations and translations, slicing and toolpath generation represent significant challenges. Slicing has been partially addressed by authors in multi-axis LMD. However, tool-path generation in multi-axis LMD is rarely touched. One of the reasons is that the required slices for LMD may be strongly non-developable. This fact produces a significant mismatch between the tool-path speeds and other parameters in Parametric space vs. actual Euclidean space. For the particular case of developable slices present in workpieces with cylindrical kernel and overhanging neighborhoods, this manuscript presents a methodology for LMD tool path generation. Our algorithm takes advantage of existing cylindrical iso-radial slicing by generating a path in the (?, z) parameter space and isometrically translating it into the R3 Euclidean space. The presented approach is advantageous because it allows the path-planning of complex structures by using the methods for conventional 2.5-axis AM. Our computer experiments show that the presented approach can be effectively used in manufacturing industrial/mechanical pieces (e.g., spur gears). Future work includes the generation of the machine g-code for actual LMD equipment.
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    Adaptation of Interaction Mechanisms in Virtual Reality Shopping Environments for People with Upper Limb Motor Difficulties
    (The Eurographics Association, 2024) Grande, Rubén; Herrera, Vanesa; Glez-Morcillo, Carlos; Reyes, Ana de los; Castro-Schez, José J.; Albusac, Javier; Marco, Julio; Patow, Gustavo; Grande, Rubén|https://orcid.org/0000-0002-0583-6865; Herrera, Vanesa|https://orcid.org/0000-0002-6187-4794; Glez-Morcillo, Carlos|https://orcid.org/0000-0002-8568-9542; Reyes, Ana de los|https://orcid.org/0000-0003-2905-2405; Castro-Schez, José J.|https://orcid.org/0000-0002-0201-7653; Albusac, Javier|https://orcid.org/0000-0003-1889-3065
    In recent years, there has been research and exploration into the development of new shopping experiences within the field of electronic commerce (e-commerce). One of the technologies that can offer a more immersive shopping experience is Virtual Reality (VR). Retail giants such as Amazon and Alibaba Group have begun to use it. The technological advancement of VR, motivated by its use in various domains like e-commerce, has driven the development of software tools like APIs which allow developers to easily develop applications for these devices. One of the latest technologies included in recent VR headsets is hand tracking, which allows users to use their own hands as an input method to interact with the virtual environment. However, software tools for the development of VR applications are not fully adapted to include accessibility options for people with motor difficulties in their bodies, making it very difficult for these people to use this technology with both controllers and hand tracking. To promote accessibility options in the use of VR shopping environments, this study will present the adaptation of a set of interaction mechanisms, among which we highlight: automatic object grabbing, release of grabbed objects, navigation through the environment, attraction of distant objects, and interaction with the shopping cart. These adaptations will be made using Meta's API for Meta Quest devices as a base. The adapted environment has been tested by healthy students from the faculty and one of them with reduced mobility in the left half of his body after suffering a stroke. In this paper, we present the feedback provided by the volunteers, as well as the verification that these interaction mechanisms meet our expectations. This is an essential previous step to carry out a planned experimental session with patients with spinal cord injuries and therapist at the National Hospital for Paraplegics in Toledo (HNPT).
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    Serious Games and Artificial Intelligence for the Detection of Mathematical Difficulties at School
    (The Eurographics Association, 2024) Hornos-Arias, Josep; Serra-Grabulosa, Josep Maria; Gómez-Berengueras, Jonathan; Grau-Carrion, Sergi; Marco, Julio; Patow, Gustavo
    Mathematical attainment at the beginning of primary school is the strongest predictor of later mathematical achievement. Mathematical difficulties are assessed objectively using screening tools based on cognitive assessment for numerical processing and calculation on an individual basis under professional supervision, which is why early detection/intervention in school is difficult to implement. Our main objective was to validate a tool that combines a serious game with machine learning (ML) algorithms to perform accurate prediction for cognitive assessment of numerical processing and calculation, facilitating early detection of unsupervised mathematical difficulties at school. Following an uncontrolled open trial with a small sample size (90 children in 2nd grade of primary school) we were able to train and compare different ML algorithms with the data generated with our serious game and traditional cognitive assessments. The best fitted models for each cognitive area offered promising results, showing accuracies between 65% and 96% that combined with other good performance metrics (high recall and F1 scores for some cases) appointed to a high fidelity on diagnose. Although the results are not totally conclusive, as this was an exploratory study and more research must be done, we were able to validate the system.
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    An adaptative Shader for Human Visual Defects Simulation
    (The Eurographics Association, 2023) Fons, Pere; Buades, Jose Maria; Perales, Franisco; Gimeno Sancho, Jesús; Comino Trinidad, Marc
    A novel programmable shader is proposed to accurately simulate the main important human visual defects under different situations in daily life. An improved model of eye model is introduced to reasonably predict the anatomical and optical properties of the human eye. This eye model is composed of an accommodation and color model, and both these models are combined to simulate the varying refractive power of the human eye and color vision deficiency. Finally, distributed ray tracing techniques is combined with this eye model to produce a variety of visual results using the programmable shader in NVIDIA OptiX environment.
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    Modal Locomotion of C. elegans
    (The Eurographics Association, 2019) Mujika, Andoni; Merino, Sara; Leškovský, Peter; Epelde, Gorka; Oyarzun, David; Otaduy, Miguel Angel; Casas, Dan and Jarabo, Adrián
    Caenorhabditis elegans (C. elegans) is a roundworm that, thanks to its combination of biological simplicity and behavioral richness, offers an excellent opportunity for initial experimentation of many human diseases. In this work, we introduce a locomotion model for C. elegans, which can enable in-silico validation of behavioral experiments prior to physical experimentation with actual C. elegans specimens. Our model enables interactive simulation of self-propelling C. elegans, using as sole input biologically inspired muscle forces and frictional contact. The key to our model is a simple locomotion control strategy that activates selected natural vibration modes of the worm. We perform an offline analysis of the natural vibration modes, select those that best match the deformation of the worm during locomotion, and design force profiles that activate these vibration modes in a coordinated manner. Together with force compensation for momentum conservation and an anisotropic friction model, we achieve locomotions that match qualitatively those of real-world worms. Our approach is general, and could be extended to the locomotion of other types of animals or characters.
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    Perfect Spatial Hashing for Point-cloud-to-mesh Registration
    (The Eurographics Association, 2019) Mejia-Parra, Daniel; Lalinde-Pulido, Juan; Sánchez, Jairo R.; Ruiz-Salguero, Oscar; Posada, Jorge; Casas, Dan and Jarabo, Adrián
    Point-cloud-to-mesh registration estimates a rigid transformation that minimizes the distance between a point sample of a surface and a reference mesh of such a surface, both lying in different coordinate systems. Point-cloud-to-mesh-registration is an ubiquitous problem in medical imaging, CAD CAM CAE, reverse engineering, virtual reality and many other disciplines. Common registration methods include Iterative Closest Point (ICP), RANdom SAmple Consensus (RANSAC) and Normal Distribution Transform (NDT). These methods require to repeatedly estimate the distance between a point cloud and a mesh, which becomes computationally expensive as the point set sizes increase. To overcome this problem, this article presents the implementation of a Perfect Spatial Hashing for point-cloud-to-mesh registration. The complexity of the registration algorithm using Perfect Spatial Hashing is O(NYxn) (NY : point cloud size, n: number of max. ICP iterations), compared to standard octrees and kd-trees (time complexity O(NY log(NT)xn), NT : reference mesh size). The cost of pre-processing is O(NT +(N3H )2) (N3H : Hash table size). The test results show convergence of the algorithm (error below 7e-05) for massive point clouds / reference meshes (NY = 50k and NT = 28055k, respectively). Future work includes GPU implementation of the algorithm for fast registration of massive point clouds.