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Now showing 1 - 10 of 63
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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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    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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    The Prose Storyboard Language: A Tool for Annotating and Directing Movies
    (The Eurographics Association, 2022) Ronfard, Rémi; Gandhi, Vineet; Boiron, Laurent; Murukutla, Vaishnavi Ameya; Ronfard, Rémi; Wu, Hui-Yin
    The prose storyboard language is a formal language for describing movies shot by shot, where each shot is described with a unique sentence. The language uses a simple syntax and limited vocabulary borrowed from working practices in traditional movie-making and is intended to be readable both by machines and humans. The language has been designed over the last ten years to serve as a high-level user interface for intelligent cinematography and editing systems. In this new paper, we present the latest evolution of the language, and the results of an extensive annotation exercise showing the benefits of the language in the task of annotating the sophisticated cinematography and film editing of classic movies.
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    An Annotation Tool for Digital Restoration of Wall Paintings
    (The Eurographics Association, 2022) Barreiro Díaz, Albert; Munoz-Pandiella, Imanol; Bosch, Carles; Andujar, Carlos; Ponchio, Federico; Pintus, Ruggero
    Antique paintings are essential to study and understand our past. Paintings, and specifically mural paintings, are delicate artworks that are affected by multiple deterioration conditions. Weathering and human interventions cause different damage problems, and physical and chemical changes degrade their visual color appearance. As a consequence, art historians and archaeologists require a huge effort to attempt to rebuild their original appearance. The annotation of digital images of the paintings is a valuable tool in this process. In this paper we analyze major requirements from art historians concerning the annotation of painting regions from the point of view of digital restoration. We also describe a tool prototype (based on TagLab) intended to facilitate the annotation and segmentation of mural paintings. The tool assists art historians in formulating multiple hypotheses on the original appearance by supporting multiple annotation layers for degradation and color, providing both hand-drawn and semi-automatic segmentation, and offering web-based dissemination and sharing of the annotations through the W3C Web Annotation Data Model.
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    Evaluation of Volume Representation Networks for Meteorological Ensemble Compression
    (The Eurographics Association, 2022) Höhlein, Kevin; Weiss, Sebastian; Necker, Tobias; Weissmann, Martin; Miyoshi, Takemasa; Westermann, Rüdiger; Bender, Jan; Botsch, Mario; Keim, Daniel A.
    Recent studies have shown that volume scene representation networks constitute powerful means to transform 3D scalar fields into extremely compact representations, from which the initial field samples can be randomly accessed. In this work, we evaluate the capabilities of such networks to compress meteorological ensemble data, which are comprised of many separate weather forecast simulations. We analyze whether these networks can effectively exploit similarities between the ensemble members, and how alternative classical compression approaches perform in comparison. Since meteorological ensembles contain different physical parameters with various statistical characteristics and variations on multiple scales of magnitude, we analyze the impact of data normalization schemes on learning quality. Along with an evaluation of the trade-offs between reconstruction quality and network model parameterization, we compare compression ratios and reconstruction quality for different model architectures and alternative compression schemes.
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    Scan2FEM: From Point Clouds to Structured 3D Models Suitable for Simulation
    (The Eurographics Association, 2022) Selman, Zain; Musto, Juan; Kobbelt, Leif; Ponchio, Federico; Pintus, Ruggero
    Preservation of cultural heritage is important to prevent singular objects or sites of cultural importance to decay. One aspect of preservation is the creation of a digital twin. In case of a catastrophic event, this twin can be used to support repairs or reconstruction, in order to stay faithful to the original object or site. Certain activities in prolongation of such an objects lifetime may involve adding or replacing structural support elements to prevent a collapse. We propose an automatic method that is capable of transforming a point cloud into a geometric representation that is suitable for structural analysis. We robustly find cuboids and their connections in a point cloud to approximate the wooden beam structure contained inside. We export the necessary information to perform structural analysis, on the example of the timber attic of the UNESCO World Heritage Aachen Cathedral. We provide evaluation of the resulting cuboids' quality and show how a user can interactively refine the cuboids in order to improve the approximated model, and consequently the simulation results.
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    Mobile and Multimodal? A Comparative Evaluation of Interactive Workplaces for Visual Data Exploration
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) León, Gabriela Molina; Lischka, Michael; Luo, Wei; Breiter, Andreas; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    Mobile devices are increasingly being used in the workplace. The combination of touch, pen, and speech interaction with mobile devices is considered particularly promising for a more natural experience. However, we do not yet know how everyday work with multimodal data visualizations on a mobile device differs from working in the standard WIMP workplace setup. To address this gap, we created a visualization system for social scientists, with a WIMP interface for desktop PCs, and a multimodal interface for tablets. The system provides visualizations to explore spatio-temporal data with consistent WIMP and multimodal interaction techniques. To investigate how the different combinations of devices and interaction modalities affect the performance and experience of domain experts in a work setting, we conducted an experiment with 16 social scientists where they carried out a series of tasks with both interfaces. Participants were significantly faster and slightly more accurate on the WIMP interface. They solved the tasks with different strategies according to the interaction modalities available. The pen was the most used and appreciated input modality. Most participants preferred the multimodal setup and could imagine using it at work. We present our findings, together with their implications for the interaction design of data visualizations.
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    Digital Reintegration of Distributed Mural Paintings at Different Architectural Phases: the Case of St. Quirze de Pedret
    (The Eurographics Association, 2022) Munoz-Pandiella, Imanol; Argudo, Oscar; Otzet, Immaculada Lorés; Comas, Joan Font; Casademont, Genís Àvila; Pueyo, Xavier; Andujar, Carlos; Ponchio, Federico; Pintus, Ruggero
    Sant Quirze de Pedret is a Romanesque church located in Cercs (Catalonia, Spain) at the foothills of the Pyrenees. Its walls harbored one of the most important examples of mural paintings in Catalan Romanesque Art. However, in two different campaigns (in 1921 and 1937) the paintings were removed using the strappo technique and transferred to museums for safekeeping. This detachment protected the paintings from being sold in the art market, but at the price of breaking the integrity of the monument. Nowadays, the paintings are exhibited in the Museu Nacional d'Art de Catalunya - MNAC (Barcelona, Catalonia) and the Museu Diocesà i Comarcal de Solsona - MDCS (Solsona, Catalonia). Some fragments of the paintings are still on the walls of the church. In this work, we present the methodology to digitally reconstruct the church building at its different phases and group the dispersed paintings in a single virtual church, commissioned by the MDCS. We have combined 3D reconstruction (LIDAR and photogrammetric using portable artificial illumination) and modeling techniques (including texture transfer between different shapes) to recover the integrity of the monument in a single 3D virtual model. Furthermore, we have reconstructed the church building at different significant historical moments and placed actual paintings on its virtual walls, based on archaeological knowledge. This set of 3D models allows experts and visitors to better understand the monument as a whole, the relations between the different paintings, and its evolution over time.
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    Could you Relax in an Artistic Co-creative Virtual Reality Experience?
    (The Eurographics Association, 2022) Lomet, Julien; Gaugne, Ronan; Gouranton, Valérie; Hideaki Uchiyama; Jean-Marie Normand
    Our work contributes to the design and study of artistic collaborative virtual environments through the presentation of immersive and interactive digital artwork installation and the evaluation of the impact of the experience on visitor's emotional state. The experience is centered on a dance performance, involves collaborative spectators who are engaged to the experience through full-body movements, and is structured in three times, a time of relaxation and discovery of the universe, a time of co-creation and a time of co-active contemplation. The collaborative artwork ''Creative Harmony'', was designed within a multidisciplinary team of artists, researchers and computer scientists from different laboratories. The aesthetic of the artistic environment is inspired by the German Romantism painting from 19th century. In order to foster co-presence, each participant of the experience is associated to an avatar that aims to represent both its body and movements. The music is an original composition designed to develop a peaceful and meditative ambiance to the universe of ''Creative Harmony''. The evaluation of the impact on visitor's mood is based on "Brief Mood Introspection Scale" (BMIS), a standard tool widely used in psychological and medical context. We also present an assessment of the experience through the analysis of questionnaires filled by the visitors. We observed a positive increase in the Positive-Tired indicator and a decrease in the Negative-Relaxed indicator, demonstrating the relaxing capabilities of the immersive virtual environment.
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    Evaluation of Deep Pose Detectors for Automatic Analysis of Film Style
    (The Eurographics Association, 2022) Wu, Hui-Yin; Nguyen, Luan; Tabei, Yoldoz; Sassatelli, Lucile; Ronfard, Rémi; Wu, Hui-Yin
    Identifying human characters and how they are portrayed on-screen is inherently linked to how we perceive and interpret the story and artistic value of visual media. Building computational models sensible towards story will thus require a formal representation of the character. Yet this kind of data is complex and tedious to annotate on a large scale. Human pose estimation (HPE) can facilitate this task, to identify features such as position, size, and movement that can be transformed into input to machine learning models, and enable higher artistic and storytelling interpretation. However, current HPE methods operate mainly on non-professional image content, with no comprehensive evaluation of their performance on artistic film. Our goal in this paper is thus to evaluate the performance of HPE methods on artistic film content. We first propose a formal representation of the character based on cinematography theory, then sample and annotate 2700 images from three datasets with this representation, one of which we introduce to the community. An in-depth analysis is then conducted to measure the general performance of two recent HPE methods on metrics of precision and recall for character detection , and to examine the impact of cinematographic style. From these findings, we highlight the advantages of HPE for automated film analysis, and propose future directions to improve their performance on artistic film content.