Browsing by Author "FALCIDIENO, BIANCA"

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    Feature Curve Extraction on Triangle Meshes
    (The Eurographics Association, 2019) Moscoso Thompson, Elia; Arvanitis, G.; Moustakas, Konstantinos; Hoang-Xuan, N.; Nguyen, E. R.; Tran, M.; Lejemble, T.; Barthe, L.; Mellado, N.; Romanengo, C.; Biasotti, S.; FALCIDIENO, BIANCA; Biasotti, Silvia and Lavoué, Guillaume and Veltkamp, Remco
    This paper presents the results of the SHREC'19 track: Feature curve extraction on triangle meshes. Given a model, the challenge consists in automatically extracting a subset of the mesh vertices that jointly represent a feature curve. As an optional task, participants were requested to send also a similarity evaluation among the feature curves extracted. The various approaches presented by the participants are discussed, together with their results. The proposed methods highlight different points of view of the problem of feature curve extraction. It is interesting to see that it is possible to deal with this problem with good results, despite the different approaches.
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    HT-based Recognition of Patterns on 3D Shapes Using a Dictionary of Mathematical Curves
    (The Eurographics Association, 2019) Romanengo, Chiara; Biasotti, Silvia; FALCIDIENO, BIANCA; Agus, Marco and Corsini, Massimiliano and Pintus, Ruggero
    Characteristic curves play a fundamental role in the way a shape is perceived and illustrated. To address the curve recognition problem on surfaces, we adopt a generalisation of the Hough Transform (HT) which is able to deal with mathematical curves. In particular, we extend the set of curves so far adopted for curve recognition with the HT and propose a new dictionary of curves to be selected as templates. In addition, we introduce rules of composition and aggregation of curves into patterns, not limiting the recognition to a single curve at a time. Our method recognises various curves and patterns, possibly compound on a 3D surface. It selects the most suitable profile in a family of curves and, deriving from the HT, it is robust to noise and able to deal with data incompleteness. The system we have implemented is open and allows new additions of curves in the dictionary of functions already available.
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    SHREC 2023: Detection of Symmetries on 3D Point Clouds Representing Simple Shapes
    (The Eurographics Association, 2023) Sipiran, Ivan; Romanengo, Chiara; Falcidieno, Bianca; Biasotti, Silvia; Arvanitis, Gerasimos; Chen, Chen; Fotis, Vlassis; He, Jianfang; Lv, Xiaoling; Moustakas, Konstantinos; Peng, Silong; Romanelis, Ioannis; Sun, Wenhao; Vlachos, Christoforos; Wu, Ziyu; Xie, Qiong; Fugacci, Ulderico; Lavoué, Guillaume; Veltkamp, Remco C.
    This paper presents the methods that participated in the SHREC 2023 track focused on detecting symmetries on 3D point clouds representing simple shapes. By simple shapes, we mean surfaces generated by different types of closed plane curves used as the directrix of a cylinder or a cone. This track aims to determine the reflective planes for each point cloud. The methods are evaluated in their capability of detecting the right number of symmetries and correctly identifying the reflective planes. To this end, we generated a dataset that contains point clouds representing simple shapes perturbed with different kinds of artefacts (such as noise and undersampling) to provide a thorough evaluation of the robustness of the algorithms.