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引用次数: 11

摘要

本文的主题是基于内容的3d对象检索。该方法基于特征向量,特征向量捕获以三角形网格表示的模型的3d形状。特征向量在平移、旋转、缩放和反射方面是不变的,在细节水平方面是鲁棒的。在特征提取之前,将每个3d对象转换(归一化)为规范的位置和方向。搜索在特征向量空间中执行,其中查询模型的特征向量用作键。本文给出了原始归一化步骤和特征向量。
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Content-based search for 3D-objects
The topic of this paper is content-based 3D-object retrieval. The approach is based on feature vectors, which capture 3D-shape of a model represented as a triangle mesh. The feature vectors are invariant with respect to translation, rotation, scaling, and reflection and robust with respect to level-of-detail. Before the feature extraction, each 3D-object is transformed (normalized) into a canonical position and orientation. The search is performed in the feature vector space in which the feature vector of a query model is used as a key. Original normalization steps and feature vectors are presented in this communication.
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