3DOR 17

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https://diglib.eg.org/handle/10.2312/2631242

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Browsing 3DOR 17 by Subject "I.3.3 [Computer Graphics]"

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    Exploiting the PANORAMA Representation for Convolutional Neural Network Classification and Retrieval
    (The Eurographics Association, 2017) Sfikas, Konstantinos; Theoharis, Theoharis; Pratikakis, Ioannis; Ioannis Pratikakis and Florent Dupont and Maks Ovsjanikov
    A novel 3D model classification and retrieval method, based on the PANORAMA representation and Convolutional Neural Networks, is presented. Initially, the 3D models are pose normalized using the SYMPAN method and consecutively the PANORAMA representation is extracted and used to train a convolutional neural network. The training is based on an augmented view of the extracted panoramic representation views. The proposed method is tested in terms of classification and retrieval accuracy on standard large scale datasets.
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    A Framework Based on Compressed Manifold Modes for Robust Local Spectral Analysis
    (The Eurographics Association, 2017) Haas, Sylvain; Baskurt, Atilla; Dupont, Florent; Denis, Florence; Ioannis Pratikakis and Florent Dupont and Maks Ovsjanikov
    Compressed Manifold Modes (CMM) were recently introduced as a solution to one of the drawbacks of spectral analysis on triangular meshes. The eigenfunctions of the Laplace-Beltrami operator on a mesh depend on the whole shape which makes them sensitive to local aspects. CMM are solutions of an extended problem that have a compact rather than global support and are thus suitable for a wider range of applications. In order to use CMM in real applications, an extensive test has been performed to better understand the limits of their computation (convergence and speed) according to the compactness parameter, the mesh resolution and the number of requested modes. The contribution of this paper is to propose a robust choice of parameters, the automated computation of an adequate number of modes (or eigenfunctions), stability with mutltiresolution and isometric meshes, and an example application with high potential for shape indexation.
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    Retrieval of Surfaces with Similar Relief Patterns
    (The Eurographics Association, 2017) Biasotti, S.; Thompson, E. Moscoso; Aono, M.; Hamza, A. Ben; Bustos, B.; Dong, S.; Du, B.; Fehri, A.; Li, H.; Limberger, F. A.; Masoumi, M.; Rezaei, M.; Sipiran, I.; Sun, L.; Tatsuma, A.; Forero, S. Velasco; Wilson, R. C.; Wu, Y.; Zhang, J.; Zhao, T.; Fornasa, F.; Giachetti, A.; Ioannis Pratikakis and Florent Dupont and Maks Ovsjanikov
    This paper presents the results of the SHREC'17 contest on retrieval of surfaces with similar relief patterns. The proposed task was created in order to verify the possibility of retrieving surface patches with a relief pattern similar to an example from a database of small surface elements. This task, related to many real world applications, requires an effective characterization of local "texture" information not depending on patch size and bending. Retrieval performances of the proposed methods reveal that the problem is not quite easy to solve and, even if some of the proposed methods demonstrate promising results, further research is surely needed to find effective relief pattern characterization techniques for practical applications.