Landscape Perspective Distance-Included Angle Shape Distribution Analysis Based on 3D CAD Model Retrieval Algorithm

In view of the results obtained in the retrieval process of the 3D CAD model, which can show the differences in the local feature details of the model, the 3D CAD model retrieval algorithm is introduced into the analysis of the perspective distance-angle shape distribution of the garden landscape in this paper. Random sampling is performed on the surface of the constructed 3D CAD model, combined with the test distance between the sampling point and the neighboring points, and the corresponding garden landscape perspective distance-angle shape distribution characteristics in this area are calculated in order to achieve the similarity of the CAD model high-speed retrieval. Finally, experimental research shows that the algorithm proposed in this paper is better than the overall shape distribution algorithm and the spherical harmonic algorithm in the search performance of the CAD model, and it can effectively improve the recognition ability of the local detailed features of the 3D CAD model.

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A Novel 3D CAD Model Retrieval Method Based on Vertices Classification and Weights Combination Optimization

Mathematical Problems in Engineering ◽

10.1155/2017/6049750 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 3

Author(s):

Ting Zhuang ◽

Xutang Zhang ◽

Zhenxiu Hou ◽

Wangmeng Zuo ◽

Yan Liu

Keyword(s):

3D Model ◽

Performance Metrics ◽

Computational Cost ◽

Retrieval Algorithm ◽

Cad Model ◽

3D Shape ◽

3D Cad ◽

Combination Optimization ◽

Model Retrieval ◽

3D Cad Model Retrieval

3D shape retrieval is a problem of current interest in different fields, especially in the mechanical engineering domain. According to our knowledge, multifeature based techniques achieve the best performance at present. However, the practicability of those methods is badly limited due to the high computational cost. To improve the retrieval efficiency of 3D CAD model, we propose a novel 3D CAD model retrieval algorithm called VSC_WCO which consists of a new 3D shape descriptor named VSC and Weights Combination Optimization scheme WCO. VSC represents a 3D model with three distance distribution histograms based on vertices classification. The weighted sum of L1 norm distances between corresponding distance histograms of two VSC descriptors is regarded as dissimilarity of two models. For higher retrieval accuracy on a classified 3D model database, WCO is proposed based on Particle Swarm Optimization and existing class information. Experimental results on ESB, PSB, and NTU databases show that the discriminative power of VSC is already comparable to or better than several typical shape descriptors. After WCO is employed, the performance of VSC_WCO is similar to the leading methods by all performance metrics and is much better by computational efficiency.

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Research on 3D CAD Model Retrieval Algorithm Based on Global and Local Similarity

2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS) ◽

10.1109/iucc/dsci/smartcns.2019.00085 ◽

2019 ◽

Author(s):

Weifang Ma ◽

Peiyan Wang ◽

Dongfeng Cai ◽

Dahan Wang

Keyword(s):

Retrieval Algorithm ◽

Local Similarity ◽

Cad Model ◽

3D Cad ◽

Model Retrieval ◽

Global And Local ◽

3D Cad Model Retrieval

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3D CAD Model Retrieval Algorithm Based on Accessibility Cone Distributions

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.834-836.1444 ◽

2013 ◽

Vol 834-836 ◽

pp. 1444-1447

Author(s):

Wei Qiang

Keyword(s):

Engineering Application ◽

Similarity Coefficient ◽

Retrieval Algorithm ◽

Cad Model ◽

3D Cad ◽

Planar Grid ◽

Model Retrieval ◽

Cad Models ◽

The Given ◽

3D Cad Model Retrieval

To reuse 3D CAD models more efficiently, a new 3D CAD model retrieval algorithm based on accessibility cone distributions is proposed. Firstly, a sufficiently large number of random sample points on surface of 3D CAD model are taken and the normal direction of each sample point is recorded. Then, the accessibility cone of the given sampled point is computed. Secondly, a planar grid is constructed to express the accessibility cone distribution by obtaining a statistic data of the sampled points. Lastly, the L1 distance metric method is taken to compute the similarity between the two accessibility cone matrices, which can give the similarity coefficient for two compared 3D CAD models. Experiments results show that the algorithm can effectively support 3D CAD model retrieval, and the efficiency meets the requirement of engineering application.

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3D CAD Model Retrieval Based on Oriented Bounding Box and Normals Distribution

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.496-500.2324 ◽

2014 ◽

Vol 496-500 ◽

pp. 2324-2327

Author(s):

Qiang Chen ◽

Yong Mei Yu

Keyword(s):

Experimental Results ◽

Cad Model ◽

Global Feature ◽

Shape Distribution ◽

3D Cad ◽

Bounding Box ◽

Model Retrieval ◽

3D Cad Model Retrieval ◽

Initial Retrieval

Shape Distribution (SD) describes the global feature of 3D CAD model which can be used to distinguish one model from others. But sometimes, different models may have the similar SD features. In this case SD is not suitable for 3D CAD model retrieval. Although two models have the same SD features, their oriented bounding box (OBB) and normals distribution may differ from each other. In this paper, a new algorithm based on OBB and normals distribution is proposed to tackle this problem. SD feature is used for initial retrieval, then OBB and normals distribution are used for fine retrieval. Experimental results indicate the efficiency and feasibility of the proposed method.

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