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3D model feature extraction algorithm based on shape weighted

机译:基于形状加权的3D模型特征提取算法

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Feature extraction is the focus of the 3D model retrieval research. Recent years, some methods for feature extraction have been proposed. Although, the extraction algorithms are increasingly complex and computational, recall and precision rate is only improved slowly. This paper proposes a novel 3D model feature extraction algorithm based on shape weighted, taking into account the distance between center point and the sample point, as well as the area of the corresponding triangular patches, and building a histogram for feature descriptor. The presented algorithm takes full advantage of the model surface information and its calculation is simple and less time consuming. Experiments show that the algorithm improves recall and precision effectively.
机译:特征提取是3D模型检索研究的重点。近年来,已经提出了一些特征提取方法。虽然,提取算法越来越复杂,并且计算,召回和精密率仅缓慢提高。本文提出了一种基于形状加权的新型3D模型特征提取算法,考虑了中心点与采样点之间的距离,以及相应三角形贴片的面积,以及构建特征描述符的直方图。呈现的算法可以充分利用模型表面信息,其计算简单且耗时较少。实验表明,该算法有效地提高了召回和精度。

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