3DOR 14

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https://diglib.eg.org/handle/10.2312/7710

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Browsing 3DOR 14 by Subject "Curve"

Now showing 1 - 5 of 5
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    3D Volume Matching for Mesh Animation of Moving Actors
    (The Eurographics Association, 2014) Blache, Ludovic; Loscos, Celine; Nocent, Olivier; Lucas, Laurent; Benjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkamp
    4D multiview reconstruction of moving actors has many applications in the entertainment industry and although studios providing such services become more accessible, efforts have to be done in order to improve the underlying technology to produce high-quality 4D contents. In this paper, we enable surface matching for an animated mesh sequence in order to introduce coherence in the data. The context is provided by an indoor multi-camera system which performs synchronized video captures from multiple viewpoints in a chroma key studio. Our input is given by a volumetric silhouette-based reconstruction algorithm that generates a visual hull at each frame of the video sequence. These 3D volumetric models differ from one frame to another, in terms of structure and topology, which makes them very difficult to use in post-production and 3D animation software solutions. Our goal is to transform this input sequence of independent 3D volumes into a single dynamic volumetric structure, directly usable in post-production. These volumes are then transformed into an animated mesh. Our approach is based on a motion estimation procedure. An unsigned distance function on the volumes is used as the main shape descriptor and a 3D surface matching algorithm minimizes the interference between unrelated surface regions. Experimental results, tested on our multiview datasets, show that our method outperforms approaches based on optical flow when considering robustness over several frames.
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    Coulomb Shapes: Using Electrostatic Forces for Deformation-invariant Shape Representation
    (The Eurographics Association, 2014) Boscaini, Davide; Girdziusas, Ramunas; Bronstein, Michael M.; Benjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkamp
    Canonical shape analysis is a popular method in deformable shape matching, trying to bring the shape into a canonical form that undoes its non-rigid deformations, thus reducing the problem of non-rigid matching into a rigid one. The canonization can be performed by measuring geodesic distances between all pairs of points on the shape and embedding them into a Euclidean space by means of multidimensional scaling (MDS), which reduces the intrinsic isometries of the shape into the extrinsic (Euclidean) isometries of the embedding space. A notable drawback of MDS-based canonical forms is their sensitivity to topological noise: different shape connectivity can affect dramatically the geodesic distances, resulting in a global distortion of the canonical form. In this paper, we propose a different shape canonization approach based on a physical model of electrostatic repulsion.We minimize the Coulomb energy subject to the local distance constraints between adjacent shape vertices. Our model naturally handles topological noise, allowing to 'tear' the shape at points of strong repulsion. Furthermore, the problem is computationally efficient, as it lends itself to fast multipole methods. We show experimental results in which our method compares favorably to MDS-based canonical forms.
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    GeoTopo: Dynamic 3D Facial Expression Retrieval Using Topological and Geometric Information
    (The Eurographics Association, 2014) Danelakis, Antonios; Theoharis, Theoharis; Pratikakis, Ioannis; Benjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkamp
    Recently, a lot of research has been dedicated to address the problem of facial expression recognition in dynamic sequences of 3D face scans. On the contrary, no research has been conducted on facial expression retrieval using dynamic 3D face scans. This paper illustrates the first results on the area of dynamic 3D facial expression retrieval. To this end, a novel descriptor is created, namely GeoTopo, capturing the topological as well as the geometric information of the 3D face scans along time. Experiments have been implemented using the angry, happy and surprise expressions of the publicly available dataset BU - 4DFE. The obtained retrieval results are very promising. Furthermore, a methodology which exploits the retrieval results, in order to achieve unsupervised dynamic 3D facial expression recognition, is presented. The aforementioned unsupervised methodology achieves classification accuracy comparable to the supervised dynamic 3D facial expression recognition state-of-the-art techniques.
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    Quantitative Comparison of Hole Filling Methods for 3D Object Search
    (The Eurographics Association, 2014) Rojas, Mario A.; Sukno, Federico M.; Waddington, John L.; Whelan, Paul F.; Benjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkamp
    Retrieval of 3D models has become an important issue due to the increase in the number of digitized objects that are available in many different fields. When stored data present defects such as holes, accurate and reliable repairing tools are needed to solve these issues. In this work we present a comparative evaluation of hole filling algorithms from the local and global perspective, measuring quantitatively the quality of the repaired meshes and describing the impact these tools have on the models. We do this by mapping holes from one mesh onto another in order to create a synthetic dataset with realistic holes and ground truth and use the Hausdorff and RMS distance, as well as the mean angular deviation, to quantify the errors. The results show that the performance at a local level is similar for all compared methods, but large differences (up to 20%) appear when viewed at a global level, where algorithms that use volumetric representations introduce significant changes in the original models.
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    Symmetry and Fourier Descriptor: A Hybrid Feature For NURBS based B-Rep Models Retrieval
    (The Eurographics Association, 2014) Dang, Quoc Viet; Morin, Geraldine; Mouysset, Sandrine; Benjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco Veltkamp
    As the number of models in 3D databases grows, an efficient 3D models indexing mechanism and a similarity measure to ease model retrieval are necessary. In this paper, we present a query-by-model framework for NURBS based B-Rep models retrieval that combines partial symmetry of the object and the Fourier shape descriptor of canonical 2D projections of the 3D models. In fact, most objects are composed by similar parts up to an isometry. By detecting the dominant partial symmetry of a given NURBS based B-Rep model, we define two canonical planes from which the Fourier descriptors are extracted to measure the similarity among 3D models.