3DOR 16

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https://diglib.eg.org/handle/10.2312/15070

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Browsing 3DOR 16 by Subject "I.3.5 [Computer Graphics]"

Now showing 1 - 7 of 7
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    A Descriptor for Voxel Shapes Based on the Skeleton Cut Space
    (The Eurographics Association, 2016) Feng, Cong; Jalba, Andrei C.; Telea, Alexandru C.; A. Ferreira and A. Giachetti and D. Giorgi
    Two-dimensional medial axes and three-dimensional curve skeletons have been long used for shape retrieval tasks. In contrast, and despite their ability to fully capture shape geometry and topology, three-dimensional surface skeletons have seen much less usage in this context. We present here a framework for shape matching and retrieval based on such surface skeletons. To this end, we construct a space of cuts generated by the surface skeleton, which has desirable invariance properties with respect to shape size, rotation, translation, pose, and noise. Next, we extract a histogram-based descriptor from this cut space, and discuss three different metrics to compare such histograms for shape retrieval. We illustrate our proposal by showing our descriptor's effectiveness in shape retrieval using a known shape-database benchmark.
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    An Edit Distance for Reeb Graphs
    (The Eurographics Association, 2016) Bauer, Ulrich; Fabio, Barbara Di; Landi, Claudia; A. Ferreira and A. Giachetti and D. Giorgi
    We consider the problem of assessing the similarity of 3D shapes using Reeb graphs from the standpoint of robustness under perturbations. For this purpose, 3D objects are viewed as spaces endowed with real-valued functions, while the similarity between the resulting Reeb graphs is addressed through a graph edit distance. The cases of smooth functions on manifolds and piecewise linear functions on polyhedra stand out as the most interesting ones. The main contribution of this paper is the introduction of a general edit distance suitable for comparing Reeb graphs in these settings. This edit distance promises to be useful for applications in 3D object retrieval because of its stability properties in the presence of noise.
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    An Experimental Shape Matching Approach for Protein Docking
    (The Eurographics Association, 2016) Fernandes, Francisco; Ferreira, Alfredo; A. Ferreira and A. Giachetti and D. Giorgi
    Proteins play a vital role in biological processes, with their function being largely determined by their structure. It is important to know what a protein binds, where it binds, how it binds, and what is its final conformation. Several methodologies have been applied to solve this complex protein-protein docking problem, but the number of degrees of freedom renders this a very slow and computationally heavy challenge. To handle this problem, we propose a multi-level space partition approach to describe the three-dimensional shape of the protein. By combining two proteins in the same data structure we are able to easily detect the shape-complementary regions. Moreover, by directly integrating bio-energetic information, we can drive the algorithm by both parameters and provide a fast and efficient way to overcome some of the limitations of previous approaches.
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    Matching of Deformable Shapes with Topological Noise
    (The Eurographics Association, 2016) Lähner, Z.; Rodolà, E.; Bronstein, M. M.; Cremers, D.; Burghard, O.; Cosmo, L.; Dieckmann, A.; Klein, R.; Sahillioglu, Y.; A. Ferreira and A. Giachetti and D. Giorgi
    A particularly challenging setting of the shape matching problem arises when the shapes being matched have topological artifacts due to the coalescence of spatially close surface regions - a scenario that frequently occurs when dealing with real data under suboptimal acquisition conditions. This track of the SHREC'16 contest evaluates shape matching algorithms that operate on 3D shapes under synthetically produced topological changes. The task is to produce a pointwise matching (either sparse or dense) between 90 pairs of shapes, representing the same individual in different poses but with different topology. A separate set of 15 shapes with ground-truth correspondence was provided as training data for learning-based techniques and for parameter tuning. Three research groups participated in the contest; this paper presents the track dataset, and describes the different methods and the contest results.
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    Partial Matching of Deformable Shapes
    (The Eurographics Association, 2016) Cosmo, L.; RodolĂ , E.; Bronstein, M. M.; Torsello, A.; Cremers, D.; Sahillioglu, Y.; A. Ferreira and A. Giachetti and D. Giorgi
    Matching deformable 3D shapes under partiality transformations is a challenging problem that has received limited focus in the computer vision and graphics communities. With this benchmark, we explore and thoroughly investigate the robustness of existing matching methods in this challenging task. Participants are asked to provide a point-to-point correspondence (either sparse or dense) between deformable shapes undergoing different kinds of partiality transformations, resulting in a total of 400 matching problems to be solved for each method - making this benchmark the biggest and most challenging of its kind. Five matching algorithms were evaluated in the contest; this paper presents the details of the dataset, the adopted evaluation measures, and shows thorough comparisons among all competing methods.
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    Shape Retrieval of Low-Cost RGB-D Captures
    (The Eurographics Association, 2016) Pascoal, Pedro B.; Proença, Pedro; Gaspar, Filipe; Dias, Miguel Sales; Ferreira, Alfredo; Tatsuma, Atsushi; Aono, Masaki; Logoglu, K. Berker; Kalkan, Sinan; Temizel, Alptekin; Li, Bo; Johan, Henry; Lu, Yijuan; Seib, Viktor; Link, Norman; Paulus, Dietrich; A. Ferreira and A. Giachetti and D. Giorgi
    RGB-D cameras allow to capture digital representations of objects in an easy and inexpensive way. Such technology enables ordinary users to capture everyday object into digital 3D representations. In this context, we present a track for the Shape Retrieval Contest, which focus on objects digitized using the latest version of Microsoft Kinect, namely, Kinect One. The proposed, track encompasses a dataset of two hundred objects and respective classification.
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    Towards an Observer-oriented Theory of Shape Comparison
    (The Eurographics Association, 2016) Frosini, Patrizio; A. Ferreira and A. Giachetti and D. Giorgi
    In this position paper we suggest a possible metric approach to shape comparison that is based on a mathematical formalization of the concept of observer, seen as a collection of suitable operators acting on a metric space of functions. These functions represent the set of data that are accessible to the observer, while the operators describe the way the observer elaborates the data and enclose the invariance that he/she associates with them. We expose this model and illustrate some theoretical reasons that justify its possible use for shape comparison.