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A Compact Multi-view Descriptor for 3D Object Retrieval

机译:用于3D对象检索的紧凑型多视图描述符

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In this paper, a novel view-based approach for 3D object retrieval is introduced. A set of 2D images (multi-views) are automatically generated from a 3D object, by taking views from uniformly distributed viewpoints. For each image, a set of 2D rotation-invariant shape descriptors is extracted. The global shape similarity between two 3D models is achieved by applying a novel matching scheme, which effectively combines the information extracted from the multiview representation. The proposed approach can well serve as a unified framework, supporting multimodal queries (such as sketches, 2D images, 3D objects). The experimental results illustrate the superiority of the method over similar view-based approaches.
机译:本文介绍了一种新颖的基于视图的3D对象检索方法。通过从均匀分布的视点获取视图,可以从3D对象自动生成一组2D图像(多视图)。对于每个图像,提取一组2D旋转不变形状描述符。通过应用新颖的匹配方案,可以有效地组合从多视图表示中提取的信息,从而实现两个3D模型之间的全局形状相似性。所提出的方法可以很好地用作统一框架,支持多模式查询(例如草图,2D图像,3D对象)。实验结果表明,该方法优于类似的基于视图的方法。

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