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Three-dimensional model comparison and search method based on nuclear density estimation

A technology of kernel density estimation and 3D model, applied in computing, special data processing applications, instruments, etc., can solve problems such as lack of topological and geometric constraint information

Inactive Publication Date: 2010-11-10
NANJING UNIV
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Problems solved by technology

The disadvantage of this type of method is that some topological and geometric constraint information of the original model is often missing in the statistical process

Method used

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  • Three-dimensional model comparison and search method based on nuclear density estimation
  • Three-dimensional model comparison and search method based on nuclear density estimation
  • Three-dimensional model comparison and search method based on nuclear density estimation

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Embodiment Construction

[0043] Such as figure 1 As shown, a kind of three-dimensional model comparison and retrieval method based on kernel density estimation of the present invention, after reading a three-dimensional model data that has n triangular faces, comprises the following steps:

[0044] Step 1, normalization of 3D model coordinate data, including: grid subdivision, 3D model translation normalization and model scaling normalization;

[0045] Step 2, extraction of 3D model features: For each pair of facets i and j in the 3D model of n facets, extract the cosine value θ of the normal angle i，j and the geodesic distance L along the surface of the 3D model i，j , forming n(n-1) / 2 feature pairs S constraint ={i，j , L i，j >|i∈[0,n-1], j∈[i+1,n]};

[0046] Step 3, feature resampling: Merge adjacent feature pairs so that the number of feature pairs is reduced from n(n-1) / 2 to n;

[0047] Step 4, Kernel Density Estimation: Perform multi-dimensional kernel density estimation to generate the chara...

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Abstract

The invention provides a three-dimensional module comparison and search method based on nuclear density estimation, which comprises the steps of normalization of three-dimensional model coordinate data, extraction of three-dimensional module characteristics, resampling of the characteristics, nuclear density estimation and three-dimensional model comparison. The normalization of the three-dimensional model coordinate data comprises gridding subdivision, translation normalization of a three-dimensional model and scaling normalization of the three-dimensional model. The resampling of the characteristics is performed by merging adjacent characteristic pairs to reduce the amount of the characteristic pairs from n (n-1) to n. The nuclear density estimation is realized by performing multidimensional density estimation to generate a characteristic distribution function of a three-dimensional model. The three-dimensional model comparison is realized by comparing the similarity of the corresponding characteristic distribution functions of three-dimensional modules by utilizing KL distance to compare and search the three-dimensional models. The nuclear density estimation has greater flexibility and generality for characteristic distribution modeling of three-dimensional models with different types and different shapes. Multidimensional nuclear density estimation can utilize abundant multidimensional shape characteristics, and can better depict the characteristics of the models compared with a method in which data with different dimensionalities are simply combined.

Description

technical field [0001] The invention relates to a method for comparing and retrieving three-dimensional models, in particular to a method for comparing and retrieving three-dimensional models based on kernel density estimation. Background technique [0002] The wide application of 3D scanning technology, 3D shape modeling and rendering software, and 3D systems in entertainment and industry has made it more urgent to retrieve the required models from a large number of 3D model libraries. Compared with traditional two-dimensional image data retrieval, due to the particularity of three-dimensional data, there are still some other challenges in its retrieval problem, such as high dimensionality, large amount of data, complex topology, and diversified model representation methods. [0003] Regarding the 3D comparison, there are two main existing methods, namely the comparison method based on topology and the comparison method based on statistics. The former transforms the model ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 路通王一鸣
Owner NANJING UNIV
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