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    Exploring Upper Limb Segmentation with Deep Learning for Augmented Virtuality
    (The Eurographics Association, 2021) Gruosso, Monica; Capece, Nicola; Erra, Ugo; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
    Sense of presence, immersion, and body ownership are among the main challenges concerning Virtual Reality (VR) and freehand-based interaction methods. Through specific hand tracking devices, freehand-based methods can allow users to use their hands for VE interaction. To visualize and make easy the freehand methods, recent approaches take advantage of 3D meshes to represent the user's hands in VE. However, this can reduce user immersion due to their unnatural correspondence with the real hands. We propose an augmented virtuality (AV) pipeline allows users to visualize their limbs in VE to overcome this limit. In particular, they were captured by a single monocular RGB camera placed in an egocentric perspective, segmented using a deep convolutional neural network (CNN), and streamed in the VE. In addition, hands were tracked through a Leap Motion controller to allow user interaction. We introduced two case studies as a preliminary investigation for this approach. Finally, both quantitative and qualitative evaluations of the CNN results were provided and highlighted the effectiveness of the proposed CNN achieving remarkable results in several real-life unconstrained scenarios.
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    Mesh Colours for Gradient Meshes
    (The Eurographics Association, 2021) Baksteen, Sarah D.; Hettinga, Gerben J.; Echevarria, Jose; Kosinka, Jiri; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
    We present an extension of the popular gradient mesh vector graphics primitive with the addition of mesh colours, aiming to reduce the mesh complexity needed to describe intricate colour gradients and textures. We present interesting applications to user-guided authoring of detailed vector graphics and image vectorisation.
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    Efficient Image Vectorisation Using Mesh Colours
    (The Eurographics Association, 2021) Hettinga, Gerben Jan; Echevarria, Jose; Kosinka, Jiri; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà, Emanuele
    Image vectorisation methods proposed in the past have not seen wide adoption due to performance, quality, controllability, and/or generality issues.We present a vectorisation method that uses mesh colours as a vector primitive for image vectorisation. We show that mesh colours have clear benefits for rendering performance and texture detail. Due to their flexibility, they also enable a simplified and more efficient generation of meshes of curved triangular patches, which are in our case constrained by our image feature extraction algorithm. The proposed method follows a standard pipeline where each step is efficient and controllable, leading to results that compare favourably with those from previous work. We show results over a variety of input images including photos, drawings, paintings, designs, and cartoons and also devise a user-guided vectorisation variant.