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Extracting The Shape Content of 3D Objects using Angle and Distance Histograms
(IEEE, 2019) Altintoprak, Sadik; Saykol, Ediz
The widespread use of 3D models in various fields such as industry, medicine, archeology and engineering lead to the importance of extracting the low-level features of 3D objects. Apart from color and texture, the shape content of 3D objects seems more difficult, hence the need for effective techniques to define the shape of the 3D model is inevitable. There are techniques in the literature to describe the shape content of objects in 3D, but most have limitations and inadequacies. In this article, we propose a technique of subtracting 3D shape content using geometric distance and angle histograms after grouping them with artificial neural networks. Performance experiments have shown that the histogram-based technique we propose here is effective for extracting the shape content of objects in the 3D plane and can be used for contextual interpretation.