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Recognizing Objects in 3D Point Clouds with Multi-Scale Local Features
Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surf...
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| Publicat a: | Sensors (Basel) |
|---|---|
| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI
2014
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4299104/ https://ncbi.nlm.nih.gov/pubmed/25517694 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s141224156 |
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