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Now showing 1 - 10 of 21
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    User Interaction Feedback in a Hand-Controlled Interface for Robot Team Tele-operation Using Wearable Augmented Reality
    (The Eurographics Association, 2017) Cannavò, Alberto; Lamberti, Fabrizio; Andrea Giachetti and Paolo Pingi and Filippo Stanco
    Continuous advancements in the field of robotics and its increasing spread across heterogeneous application scenarios make the development of ever more effective user interfaces for human-robot interaction (HRI) an extremely relevant research topic. In particular, Natural User Interfaces (NUIs), e.g., based on hand and body gestures, proved to be an interesting technology to be exploited for designing intuitive interaction paradigms in the field of HRI. However, the more sophisticated the HRI interfaces become, the more important is to provide users with an accurate feedback about the state of the robot as well as of the interface itself. In this work, an Augmented Reality (AR)-based interface is deployed on a head-mounted display to enable tele-operation of a remote robot team using hand movements and gestures. A user study is performed to assess the advantages of wearable AR compared to desktop-based AR in the execution of specific tasks.
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    A Virtual Character Posing System based on Reconfigurable Tangible User Interfaces and Immersive Virtual Reality
    (The Eurographics Association, 2018) Cannavò, A.; Lamberti, F.; Livesu, Marco and Pintore, Gianni and Signoroni, Alberto
    Computer animation and, particularly, virtual character animation, are very time consuming and skill-intensive tasks, which require animators to work with sophisticated user interfaces. Tangible user interfaces (TUIs) already proved to be capable of making character animation more intuitive, and possibly more efficient, by leveraging the affordances provided by physical props that mimic the structure of virtual counterparts. The main downside of existing TUI-based animation solutions is the reduced accuracy, which is due partly to the use of mechanical parts, partly to the fact that, despite the adoption of a 3D input, users still have to work with a 2D output (usually represented by one or more views displayed on a screen). However, output methods that are natively 3D, e.g., based on virtual reality (VR), have been already exploited in different ways within computer animation scenarios. By moving from the above considerations and by building upon an existing work, this paper proposes a VR-based character animation system that combines the advantages of TUIs with the improved spatial awareness, enhanced visualization and better control on the observation point in the virtual space ensured by immersive VR. Results of a user study with both skilled and unskilled users showed a marked preference for the devised system, which was judged as more intuitive than that in the reference work, and allowed users to pose a virtual character in a lower time and with a higher accuracy.
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    An Interactive Tuning Method for Generator Networks Trained by GAN
    (The Eurographics Association, 2022) Zhou, Mengyuan; Yamaguchi, Yasushi; Cabiddu, Daniela; Schneider, Teseo; Allegra, Dario; Catalano, Chiara Eva; Cherchi, Gianmarco; Scateni, Riccardo
    The recent studies on GAN achieved impressive results in image synthesis. However, they are still not so perfect that output images may contain unnatural regions. We propose a tuning method for generator networks trained by GAN to improve their results by interactively removing unexpected objects and textures or changing the object colors. Our method could find and ablate those units in the generator networks that are highly related to the specific regions or their colors. Compared to the related studies, our proposed method can tune pre-trained generator networks without relying on any additional information like segmentation-based networks. We built the interactive system based on our method, capable of tuning the generator networks to make the resulting images as expected. The experiments show that our method could remove only unexpected objects and textures. It could change the selected area color as well. The method also gives us some hints to discuss the properties of generator networks which layers and units are associated with objects, textures, or colors.
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    Creating Adaptive and Interactive Stories in Mixed Reality
    (The Eurographics Association, 2022) Frau, Vittoria; Serra, Sergio; Spano, Lucio Davide; Cabiddu, Daniela; Schneider, Teseo; Allegra, Dario; Catalano, Chiara Eva; Cherchi, Gianmarco; Scateni, Riccardo
    The following paper proposes the study, the design and the preliminary development of a solution for supporting users without programming experience in creating stories in a Mixed Reality environment. We focus on a Mixed Reality interface split into two parts: the creation and observation phases. During the creation phase, the end user can build his/her own story in the immersive mode of the Mixed Reality experience. The user can also enjoy the stories that other users have designed by seeing the characters appear in their surrounding environment.
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    IMGD: Image-based Multiscale Global Descriptors of Airborne LiDAR Point Clouds Used for Comparative Analysis
    (The Eurographics Association, 2021) Sreevalsan-Nair, Jaya; Mohapatra, Pragyan; Singh, Satendra; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
    Both geometric and semantic information are required for a complete understanding of regions acquired as three-dimensional (3D) point clouds using the Light Detection and Ranging (LiDAR) technology. However, the global descriptors of such datasets that integrate both the information types are rare. With a focus on airborne LiDAR point clouds, we propose a novel global descriptor that transforms the point cloud from Cartesian to barycentric coordinate spaces. We use both the probabilistic geometric classification, aggregated from multiple scales, and the semantic classification to construct our descriptor using point rendering. Thus, we get an image-based multiscale global descriptor, IMGD. To demonstrate its usability, we propose the use of distribution distance measures between the descriptors for comparing the point clouds. Our experimental results demonstrate the effectiveness of our descriptor, when constructed of publicly available datasets, and on applying our selected distance measures.
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    A 3 Cent Recognizer: Simple and Effective Retrieval and Classification of Mid-air Gestures from Single 3D Traces
    (The Eurographics Association, 2017) Caputo, Fabio Marco; Prebianca, Pietro; Carcangiu, Alessandro; Spano, Lucio D.; Giachetti, Andrea; Andrea Giachetti and Paolo Pingi and Filippo Stanco
    In this paper we present a simple 3D gesture recognizer based on trajectory matching, showing its good performances in classification and retrieval of command gestures based on single hand trajectories. We demonstrate that further simplifications in porting the classic "1 dollar" algorithm approach from the 2D to the 3D gesture recognition and retrieval problems can result in very high classification accuracy and retrieval scores even on datasets with a large number of different gestures executed by different users. Furthermore, recognition can be good even with heavily subsampled path traces and with incomplete gestures.
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    ReVize: A Library for Visualization Toolchaining with Vega-Lite
    (The Eurographics Association, 2019) Hogräfer, Marius; Schulz, Hans-Jörg; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    The field of tools for data visualization has been growing in recent years, with each tool contributing new ways to create and work with visualizations, and each offering a specialized set of features, interaction metaphors and user interfaces. This means on one hand that users have a wide choice in visualization tools. On the other hand, though, this choice might also lock-in the user: Once made, it becomes difficult and sometimes even impossible to switch to another tool - e.g., to further refine a visualization made in one tool inside another. In turn, users are forced to work around any shortcomings of the chosen tool, as switching to another tool is even more cumbersome. In this paper, we introduce ReVize, an open-source library for visualization toolchaining. ReVize makes use of Vega-Lite as a common exchange format to be able to add toolchain support to web-based tools. In contrast to existing approaches, this solution to visualization toolchaining allows for authoring a visualization with multiple tools in a back-and-forth fashion, without a preset order in which tools are to be used. We demonstrate ReVize by adding toolchain support to three existing tools - KNIME, ColorBrewer, and VisFlow - for using them in concert to author visualizations.
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    Motion Data and Model Management for Applied Statistical Motion Synthesis
    (The Eurographics Association, 2019) Herrmann, Erik; Du, Han; Antakli, André; Rubinstein, Dmitri; Schubotz, René; Sprenger, Janis; Hosseini, Somayeh; Cheema, Noshaba; Zinnikus, Ingo; Manns, Martin; Fischer, Klaus; Slusallek, Philipp; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    Machine learning based motion modelling methods such as statistical modelling require a large amount of input data. In practice, the management of the data can become a problem in itself for artists who want to control the quality of the motion models. As a solution to this problem, we present a motion data and model management system and integrate it with a statistical motion modelling pipeline. The system is based on a data storage server with a REST interface that enables the efficient storage of different versions of motion data and models. The database system is combined with a motion preprocessing tool that provides functions for batch editing, retargeting and annotation of the data. For the application of the motion models in a game engine, the framework provides a stateful motion synthesis server that can load the models directly from the data storage server. Additionally, the framework makes use of a Kubernetes compute cluster to execute time consuming processes such as the preprocessing and modelling of the data. The system is evaluated in a use case for the simulation of manual assembly workers.
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    STRONGER: Simple TRajectory-based ONline GEsture Recognizer
    (The Eurographics Association, 2021) Emporio, Marco; Caputo, Ariel; Giachetti, Andrea; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
    In this paper, we present STRONGER, a client-server solution for the online gesture recognition from captured hands' joints sequences. The system leverages a CNN-based recognizer improving current state-of-the-art solutions for segmented gestures classification, trained and tested for the online gesture recognition task on a recent benchmark including heterogeneous gestures. The recognizer provides good classification accuracy and a limited number of false positives on most of the gesture classes of the benchmark used and has been used to create a demo application in a Mixed Reality scenario using an Hololens 2 optical see through Head-Mounted Display with hand tracking capability.
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    Design and Implementation of a Visualization Tool for the in-depth Analysis of the Domestic Electricity Consumption
    (The Eurographics Association, 2019) Merlin, Gabriele; Ortu, Daniele; Cherchi, Gianmarco; Scateni, Riccardo; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    In this poster, we present a visualization tool for the in-depth analysis of domestic electricity consumption. The web-interface allows users to visualize their electricity consumption, compare them with their own records or with the means of selected communities.