Comparison of HK and SC curvature descriptions in a scale-space for the purpose of 3D object recognition

E. Akagunduz, ilkay Ulusoy
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Abstract

Most 3D object recognition methods use mean-Gaussian curvatures (HK) [2] or shape index-curvedness (SC) [2] values for classification. Although these two curvature descriptions classify objects into same categories, their mathematical defintions vary. In this study a comparison between the two curvature description is carried out for the purpose of 3D object recognition. Since unlike S; H, K and C values are not invariant of scale and resolution, a method to set them fully invariant to any transforation is proposed. The results show that scale and resolution invariant HK curvature values gives better recognition results compared to SC curvature values.
尺度空间中HK和SC曲率描述的比较,用于三维物体识别
大多数三维物体识别方法使用平均高斯曲率(HK)[2]或形状指数弯曲度(SC)[2]值进行分类。虽然这两种曲率描述将物体归为同一类,但它们的数学定义不同。本研究将两种曲率描述进行比较,用于三维物体识别。因为不像S;H、K和C值在尺度和分辨率上不是不变的,提出了一种使它们对任何变换都完全不变的方法。结果表明,尺度和分辨率不变的HK曲率值比SC曲率值具有更好的识别效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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