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This paper describes a novel method for retrieving 3D models. Following the principle of compound-eye vision, the proposed method represents a 3D model as a spherical image, and discriminates different 3D models using their corresponding spherical images. Meanwhile, by borrowing the concept of the Scale-Invariant Feature Transform (SIFT) algorithm, we design a feature extraction algorithm, named Spherical-SIFT,...
An effective method for retrieving 3D models is to represent and discriminate them with their 2D images projected from multiple viewpoints. Such view-based methods conform more closely to human visual recognition for 3D model retrieval, since the human retina essentially captures 2D images. However, most of the existing view-based methods do not take into account that different views have different...
This paper describes a new 3D model retrieval approach based on shape distributions, which represents a 3D shape as three D2 shape histograms. First, generate a sufficiently large number of random sample points on surface of 3D model and note the normal of each point. Second, we adopt the D2 shape function to measures the distance between two random points on the surface of the model, at the same...
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