一种基于内容的三维医学模型局部特征提取方法

L. Bergamasco, Fátima L. S. Nunes
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引用次数: 10

摘要

三维模型在我们的社会中被广泛使用。全局形状描述符由于其鲁棒性和易于实现的特点,在基于内容的图像检索(CBIR)中得到了广泛的应用,但这种描述符并不适合具有特定特征的检索模型。本文提出了一种局部描述符,分析三维模型在物体不同位置的形状,以提高检索精度。我们的方法比较了一个全局描述符,距离直方图,使用通用模型和特定模型的形状变形在特定区域。结果表明,我们的方法在这两种情况下都具有更高的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new local feature extraction approach for content-based 3D medical model retrieval using shape descriptor
Three-dimensional models are being extensively used in our society. Global shape descriptors are more frequently used in the Content-Based Image Retrieval (CBIR) context due to their robustness and easy implementation, but this kind of descriptor is not adequate for retrieval models with specific characteristics. In this paper a local descriptor is proposed, which analyzes the 3D model shape in different locations of the object in order to increase the retrieval accuracy. Our method is compared with a global descriptor, Distance Histogram, using generic models and specific models which have shape deformations in specific areas. Results show that our method presented higher performance in both contexts.
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