3D model retrieval using MeshSIFT descriptor and fuzzy C-means clustering
A huge number of three-dimensional models exists on the internet, due to the fact that there are now more three-dimensional modelling and digitizing tools available for ever-increasing applications. The procedures for retrieval of three-dimensional models have thus become even more essential. The su...
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| Main Authors: | , , |
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| Other Authors: | |
| Format: | EJournal Article |
| Published: |
Institute of Advanced Engineering and Science,
2020-09-01.
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| Subjects: | |
| Online Access: | Get fulltext |
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| Summary: | A huge number of three-dimensional models exists on the internet, due to the fact that there are now more three-dimensional modelling and digitizing tools available for ever-increasing applications. The procedures for retrieval of three-dimensional models have thus become even more essential. The subject of this paper is a shape retrieval of 3D models that are signified as triangle meshes. We propose a new method which first computes the descriptor of 3D models through extracting its features, and then divides a model into clusters depending on a descriptor which is invariant to scale and orientation. A Fuzzy C-means clustering method is utilized for dividing the model into clusters. The superior performance and benefits of our method are shown in the results. |
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| Item Description: | https://ijeecs.iaescore.com/index.php/IJEECS/article/view/20811 |