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Эта публикация цитируется в 9 научных статьях (всего в 9 статьях)
ОБРАБОТКА ИЗОБРАЖЕНИЙ, РАСПОЗНАВАНИЕ ОБРАЗОВ
Segmentation of 3D meshes combining the artificial neural network classifier and the spectral clustering
Fatima Rafii Zakania, Mohcine Bouksima, Khadija Arhida, Mohamed Aboulfatahb, Taoufiq Gadia a Laboratory of Informatics, Imaging, and Modeling of Complex Systems (LIIMSC) Faculty of Sciences and Techniques,
Hassan 1st University, Settat, Morocco
b Laboratory of Analysis of Systems and Treatment of Information (LASTI) Faculty of Sciences and Techniques, Hassan 1st University, Settat, Morocco
Аннотация:
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.
Ключевые слова:
3D shapes, segmentation, artificial neural networks, spectral clustering.
Поступила в редакцию: 02.12.2017 Принята в печать: 03.04.2018
Образец цитирования:
Fatima Rafii Zakani, Mohcine Bouksim, Khadija Arhid, Mohamed Aboulfatah, Taoufiq Gadi, “Segmentation of 3D meshes combining the artificial neural network classifier and the spectral clustering”, Компьютерная оптика, 42:2 (2018), 312–319
Образцы ссылок на эту страницу:
https://www.mathnet.ru/rus/co509 https://www.mathnet.ru/rus/co/v42/i2/p312
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Страница аннотации: | 245 | PDF полного текста: | 66 | Список литературы: | 22 |
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