A Compact Multi-view Descriptor for 3D Object Retrieval

P. Daras, A. Axenopoulos
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引用次数: 59

Abstract

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.
用于三维对象检索的紧凑多视图描述符
本文提出了一种基于视图的三维目标检索方法。通过从均匀分布的视点获取视图,从3D对象自动生成一组2D图像(多视图)。对于每张图像,提取一组二维旋转不变性形状描述子。采用一种新的匹配方案,有效地结合多视图表示中提取的信息,实现了两个三维模型之间的全局形状相似度。所提出的方法可以很好地作为一个统一的框架,支持多模式查询(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。
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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