Shape distribution-based retrieval of 3D CAD models at different levels of detail

Kim, Hyungki; Cha, Moohyun; Mun, Duhwan

doi:10.1007/s11042-016-3881-5

Cited by 16 publications

(4 citation statements)

References 23 publications

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“…Feature extraction based on geometric shape allows for the more comprehensive extraction of high-level information from the models. [23] However, most methods require complex computations and slow conversion speeds due to the need for model transformation. Additionally, they require a significant amount of storage space.…”

Section: Related Workmentioning

confidence: 99%

Similarity Measurement and Retrieval of Three-Dimensional Voxel Model Based on Symbolic Operator

He,

Liu,

Zhang

2024

IJGI

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Three-dimensional voxel models are widely applied in various fields such as 3D imaging, industrial design, and medical imaging. The advancement of 3D modeling techniques and measurement devices has made the generation of three-dimensional models more convenient. The exponential increase in the number of 3D models presents a significant challenge for model retrieval. Currently, these models are numerous and typically represented as point clouds or meshes, resulting in sparse data and high feature dimensions within the retrieval database. Traditional methods for 3D model retrieval suffer from high computational complexity and slow retrieval speeds. To address this issue, this paper combines spatial-filling curves with octree structures and proposes a novel approach for representing three-dimensional voxel model sequence data features, along with a similarity measurement method based on symbolic operators. This approach enables efficient similarity calculations and rapid dimensionality reduction for the three-dimensional model database, facilitating efficient similarity calculations and expedited retrieval.

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Section: Related Workmentioning

confidence: 99%

Similarity Measurement and Retrieval of Three-Dimensional Voxel Model Based on Symbolic Operator

He,

Liu,

Zhang

2024

IJGI

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“…Hong et al [33] employed shape distribution graph for overall CAD shape comparison. Kim [4] also adopted shape distribution features for mechanical CAD model retrieval.…”

Section: Cad Model Matchingmentioning

confidence: 99%

“…How to discover the target partial model quickly in the complex PPM under the interference of similar local structure has not been studied. Current content-based 3D&CAD model matching methods mainly focus on shape similarity between models [3], [4]. The extracted features are compressed shape representation of 3D&CAD models, and the results mainly reveal the shape similarities.…”

Section: Introductionmentioning

confidence: 99%

Partial Matching of Large Scale Process Plant Models Using Random Walk on Graphs

Mao

Dai

et al. 2020

IEEE Access

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3D process plant models(PPMs) in the process industry normally consists of thousands of components. And, there are many similar local structures in the PPM. Due to the complex process flow, the topology relationship among components is very complicated. Therefore, designing a new PPM is quite time consuming. In order to shorten the design cycle, content based model retrieval for PPMs is an imperative requirement. In this paper, we propose a partial matching framework for PPMs based on graph matching aiming at improving design efficiency and realizing design reuse. The random walk algorithm is employed to distinguish similar local structures. Specifically, each PPM is represented by an undirected labeled graph. The local topological feature of each component is extracted based on the random walk algorithm. For partial matching, a subgraph isomorphism algorithm is introduced. The matching process is accelerated by using the local topological feature to generate an optimized initial state and alleviate the computation of feasible rules. Experimental results show the feasibility and effectiveness of our matching framework.

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“…In geometry-based approach, feature vector is extracted from 3D model's shape and topology. Then, feature vector is used to compute model similarity [2,3]. In graph-based approach, graph is applied to describe how 3D model's shape components are linked together.…”

Section: Introductionmentioning

confidence: 99%

Similarity Calculation of 3D Model By Integrating Improved ACO Into HNN

Gao

Zhang

2020

IEEE Access

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It is important for 3D model retrieval to compute similarity between two models accurately. In order to calculate two models' similarity, their face matching scheme need be found. Hopfield neural network (HNN) and ant colony optimization (ACO) algorithm can be used to match source faces and target ones. But, they all drop into local optimum easily and can not get optimal face matching scheme. This paper proposes a new method of computing model similarity by integrating improved ACO algorithm into HNN. Shape similarity between source face and target one is calculated based on the difference of face's edge number. Structure similarity is computed according to adjacency correspondence relationship between source face and target one. Two faces' similarity is calculated based on shape similarity and structure similarity, which is introduced into transfer probability. Indirect expectation heuristic is defined to improve ACO algorithm. Then, improved ACO algorithm is integrated into HNN to search for optimal face matching scheme. Model similarity is computed based on optimal sequence of face pairs. Experimental results show that compared with improved ACO algorithm, the proposed method improves the ranking effect of 14.29% of models, which can measure two models' difference effectively.

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Shape distribution-based retrieval of 3D CAD models at different levels of detail

Cited by 16 publications

References 23 publications

Similarity Measurement and Retrieval of Three-Dimensional Voxel Model Based on Symbolic Operator

Similarity Measurement and Retrieval of Three-Dimensional Voxel Model Based on Symbolic Operator

Partial Matching of Large Scale Process Plant Models Using Random Walk on Graphs

Similarity Calculation of 3D Model By Integrating Improved ACO Into HNN

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