An Efficient Hierarchical 3D Mesh Segmentation Using Negative Curvature and Dihedral Angle

Arhid, Khadija; Zakani, Fatima Rafii; Bouksim, Mohcine; Mohamed, Azah; Gadi, Taoufiq

doi:10.22266/ijies2017.1031.16

Cited by 10 publications

(6 citation statements)

References 28 publications

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“…1 shows the obtained results. As can be seen from the obtained results, the curve obtained using learning-based approach (LB) [30] gives once again a very good classification performance by being classified at the top of the automatic segmentation algorithms, followed by the Randomized Cut algorithm (RC) [31] which slightly superforms the approach based on spectral clustering (SC) [34]. In addition, the learning-based ap-proach(LB) [30] offers a gain in operating time compared to the Randomized Cuts algorithm (RC) [31], which is costly in terms of response time of the different random segmentations it based.…”

Section: Our Proposed Approachmentioning

confidence: 92%

A novel approach for partial shape matching and similarity based on data envelopment analysis

et al. 2019

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Due to the growing number of 3D objects in digital libraries, the task of searching and browsing models in an extensive 3D database has been the focus of considerable research in the area. In the last decade, several approaches to retrieve 3D models based on shape similarity have been proposed. The majority of the existing methods addresses the problem of similarity between objects as a global matching problem. Consequently, most of these techniques do not support a part of the object as a query, in addition to their poor performance for classes with globally non-similar shape models and also for articulated objects. The partial matching technique seems to be a suitable solution to these problems. In this paper, we address the problem of shape matching and retrieval. We propose a new approach based on partial matching in which each 3D object is segmented into its constituent parts, and shape descriptors are computed from these elements to compare similarities. Several experiments investigated that our technique enables fast computing for content-based 3D shape retrieval and significantly improves the results of our method based on Data Envelopment Analysis descriptor for global matching.

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Section: Our Proposed Approachmentioning

confidence: 92%

A novel approach for partial shape matching and similarity based on data envelopment analysis

et al. 2019

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“…Then a heterogeneous graph is created by merging the weighted graph based on adjacency of patches of an initial oversegmentation and the weighted dual mesh graph. Recently in [5], our research team propose a new approach for 3D mesh segmentation that takes into account the concave and convex regions, based on the dihedral angles and negative curvatures for generating the adjacency matrix and the spectral clustering as a criterion of partitioning.…”

Section: Related Workmentioning

confidence: 99%

“…In the last decades, several techniques of 3D segmentation have been developed [3]. Among different 3D segmentation approaches, spectral clustering methods [4,5] and learning approaches [6] are the most relevant and have several beneficial features in practical applications. They make the formulation of the problem more flexible and the computation more efficient.…”

Section: Introductionmentioning

confidence: 99%

Segmentation of 3D meshes combining the artificial neural network classifier and the spectral clustering

Zakani¹,

Bouksim²,

Arhid³

et al. 2018

Computer Optics

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3D mesh segmentation has become an essential step in many applications in 3D shape analysis. In this paper, a new segmentation method is proposed based on a learning approach using the artificial neural networks classifier and the spectral clustering for segmentation. Firstly, a training step is done using the artificial neural network trained on existing segmentation, taken from the ground truth segmentation (done by humane operators) available in the benchmark proposed by Chen et al. to extract the candidate boundaries of a given 3D-model based on a set of geometric criteria. Then, we use this resulted knowledge to construct a new connectivity of the mesh and use the spectral clustering method to segment the 3D mesh into significant parts. Our approach was evaluated using different evaluation metrics. The experiments confirm that the proposed method yields significantly good results and outperforms some of the competitive segmentation methods in the literature.

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“…Existing approaches for wireframe extraction from polygonal mesh rely on local shape properties, such as surface curvatures [14] and angles between faces/vertices [1]. These shape properties are too local to capture the global structure of 3D meshes, yielding unsatised feature extraction results.…”

Section: Introductionmentioning

confidence: 99%

A Customizable VR System Supporting Industrial Equipment Operator Training

Giannini¹,

Lupinetti²,

Monti³

et al. 2022

CADandA

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Extracting wireframes from 3D meshes is a challenging problem. Existing methods are typically based on analyzing local shape properties, such as surface curvatures and angles between faces, which are generally sensitive to small features in the model and the complexity of the object. In this work, we propose a wireframe extraction method based on a geometric approximation of 3D meshes. Our idea is to utilize a well-established variational geometric partitioning method to derive a complete set of descriptive feature curves. The advantage of this strategy is that a reliable feature ltering mechanism can be inherently incorporated into the geometric approximation step, giving rise to descriptive wireframes that capture global structures of the 3D meshes. We experimented on various meshes. The results demonstrated that our method is superior to existing approaches in terms of the correctness and completeness of the extracted feature curves.

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An Efficient Hierarchical 3D Mesh Segmentation Using Negative Curvature and Dihedral Angle

Cited by 10 publications

References 28 publications

A novel approach for partial shape matching and similarity based on data envelopment analysis

A novel approach for partial shape matching and similarity based on data envelopment analysis

Segmentation of 3D meshes combining the artificial neural network classifier and the spectral clustering

A Customizable VR System Supporting Industrial Equipment Operator Training

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