A large number of 3D models are created on computers and available for networks. Some content-based retrieval technologies are indispensable to find out particular data from such anonymous datasets. Though several sha...A large number of 3D models are created on computers and available for networks. Some content-based retrieval technologies are indispensable to find out particular data from such anonymous datasets. Though several shape retrieval technologies have been developed, little attention has been given to the points on human＇s sense and impression （as known as Kansei） in the conventional techniques, In this paper, the authors propose a novel method of shape retrieval based on shape impression of human＇s Kansei. The key to the method is the Gaussian curvature distribution from 3D models as features for shape retrieval. Then it classifies the 3D models by extracted feature and measures similarity among models in storage.展开更多
We develop a data driven method(probability model) to construct a composite shape descriptor by combining a pair of scale-based shape descriptors. The selection of a pair of scale-based shape descriptors is modeled as...We develop a data driven method(probability model) to construct a composite shape descriptor by combining a pair of scale-based shape descriptors. The selection of a pair of scale-based shape descriptors is modeled as the computation of the union of two events, i.e.,retrieving similar shapes by using a single scale-based shape descriptor. The pair of scale-based shape descriptors with the highest probability forms the composite shape descriptor. Given a shape database, the composite shape descriptors for the shapes constitute a planar point set.A VoR-Tree of the planar point set is then used as an indexing structure for efficient query operation. Experiments and comparisons show the effectiveness and efficiency of the proposed composite shape descriptor.展开更多
By using the generalized Gaussian density model, this letter puts forward a new shape retrieval way based on the wavelet coefficients. Experimental results show that the proposed shape feature description is superior ...By using the generalized Gaussian density model, this letter puts forward a new shape retrieval way based on the wavelet coefficients. Experimental results show that the proposed shape feature description is superior to the traditional invariant moment algorithm. Moreover, this algorithm provides the important invariant trait to image's size and rotation, which can retrieve images based on shape with more similar results comparing with invariant moment method.展开更多
Artificial intelligence and computer vision need methods for 2D （two-dimensional） shape retrieval having discrete set of boundary points. A novel method of MHR （Hurwitz-Radon Matrices） is used in shape modeling. P...Artificial intelligence and computer vision need methods for 2D （two-dimensional） shape retrieval having discrete set of boundary points. A novel method of MHR （Hurwitz-Radon Matrices） is used in shape modeling. Proposed method is based on the family of MHR which possess columns composed of orthogonal vectors. 2D curve is retrieved via different functions as probability distribution functions： sine, cosine, tangent, logarithm, exponent, arcsin, arccos, arctan and power function. Created from the family of N-1 MHR and completed with the identical matrix, system of matrices is orthogonal only for dimensions N = 2, 4 or 8. Orthogonality of columns and rows is very significant for stability and high precision of calculations. MHR method is interpolating the function point by point without using any formula of function. Main features of MHR method are： accuracy of curve reconstruction depending on number of nodes and method of choosing nodes, interpolation of L points of the curve is connected with the computational cost of rank O（L）, MHR interpolation is not a linear interpolation.展开更多
The matching and retrieval of the 2D shapes are challenging issues in object recognition and computer vision. In this paper, we propose a new object contour descriptor termed ECPDH (Elliptic Contour Points Distributio...The matching and retrieval of the 2D shapes are challenging issues in object recognition and computer vision. In this paper, we propose a new object contour descriptor termed ECPDH (Elliptic Contour Points Distribution Histogram), which is based on the distribution of the points on an object contour under the polar coordinates. ECPDH has the essential merits of invariance to scale and translation. Dynamic Programming (DP) algorithm is used to measure the distance between the ECPDHs. The effectiveness of the proposed method is demonstrated using some standard tests on MPEG-7 shape database. The results show the precision and recall of our method over other recent methods in the literature.展开更多
Feature analysis plays a significant role in computer vision and computer graphics.In the task of shape retrieval,shape descriptor is indispensable.In recent years,feature extraction based on deep learning becomes ver...Feature analysis plays a significant role in computer vision and computer graphics.In the task of shape retrieval,shape descriptor is indispensable.In recent years,feature extraction based on deep learning becomes very popular,but the design of geometric shape descriptor is still meaningful due to the contained intrinsic information and interpretability.This paper proposes an effective and robust descriptor of 3D models.The descriptor is constructed based on the probability distribution of the normalized eigenfunctions of the Laplace–Beltrami operator on the surface,and a spectrum method for dimensionality reduction.The distance metric of the descriptor space is learned by utilizing the joint Bayesian model,and we introduce a matrix regularization in the training stage to re-estimate the covariance matrix.Finally,we apply the descriptor to 3D shape retrieval on a public benchmark.Experiments show that our method is robust and has good retrieval performance.展开更多
A method of shape encoding and retrieval is proposed in this letter, which uses centripetal code to encode shape and extracts shape's convex for retrieval. For the rotation invariance and translation invariance of...A method of shape encoding and retrieval is proposed in this letter, which uses centripetal code to encode shape and extracts shape's convex for retrieval. For the rotation invariance and translation invariance of the centripetal code and the normalization of convex,the proposed retrieval method is similarity transform resistant, Experimental results confirm this capability.展开更多
To reuse and share the valuable knowledge embedded in repositories of engineering models for accelerating the design process, improving product quality, and reducing costs, it is crucial to devise search engines capab...To reuse and share the valuable knowledge embedded in repositories of engineering models for accelerating the design process, improving product quality, and reducing costs, it is crucial to devise search engines capable of matching 3D models efficiently and effectively. In this paper, an enhanced shape distributions-based technique of using geometrical and topological information to search 3D engineering models represented by polygonal meshes was presented. A simplification method of polygonal meshes was used to simplify engineering model as the pretreatment for generation of sample points. The method of sampling points was improved and a pair of functions that was more sensitive to shape was employed to construct a 2D shape distribution. Experiments were conducted to evaluate the proposed algorithm utilizing the Engineering Shape Benchmark (ESB) database. The experiential results suggest that the search effectiveness is significantly improved by enforcing the simplification and enhanced shape distributions to engineering model retrieval.展开更多
Fourier Descriptors（FD） has been widely used in image analysis and computer vision for shape recognition as they can be made independent of translation,rotation,as well as scaling.They have also been used for develo...Fourier Descriptors（FD） has been widely used in image analysis and computer vision for shape recognition as they can be made independent of translation,rotation,as well as scaling.They have also been used for developing methods for the analysis and synthesis of four-bar linkages for path generation.This paper focuses on a comparative study of Fourier descriptors derived from various shape signatures of planar closed curves.This includes representations based on Cartesian coordinates,centroid distance,cumulative angle,and curvature.The comparison is conducted not only using commonly used criteria for shape representation and identification but also in the context of shape based retrieval of kinematic constraints for task centered mechanism design.Examples are provided to seek to extract geometric constraints such as circle,circular arc,ellipse and line-segment from a given motion.展开更多
We propose a unified 3D flow frameworkfor joint learning of shape embedding and deformationfor different categories. Our goal is to recovershapes from imperfect point clouds by fitting thebest shape template in a shape...We propose a unified 3D flow frameworkfor joint learning of shape embedding and deformationfor different categories. Our goal is to recovershapes from imperfect point clouds by fitting thebest shape template in a shape repository afterdeformation. Accordingly, we learn a shape embeddingfor template retrieval and a flow-based network forrobust deformation. We note that the deformationflow can be quite different for different shapecategories. Therefore, we introduce a novel multi-hubmodule to learn multiple modes of deformation toincorporate such variation, providing a network whichcan handle a wide range of objects from differentcategories. The shape embedding is designed to retrievethe best-fit template as the nearest neighbor in a latentspace. We replace the standard fully connected layerwith a tiny structure in the embedding that significantlyreduces network complexity and further improvesdeformation quality. Experiments show the superiorityof our method to existing state-of-the-art methods viaqualitative and quantitative comparisons. Finally, ourmethod provides efficient and flexible deformation thatcan further be used for novel shape design.展开更多
Using a group of ellipses to approach the shape contour, a new shape retrieval method is presented in this paper. In order to keep shape-based retrieval invariant to its position, orientation and size, the shape norma...Using a group of ellipses to approach the shape contour, a new shape retrieval method is presented in this paper. In order to keep shape-based retrieval invariant to its position, orientation and size, the shape normalization method is presented. From our research, any closed shape contour can be uniquely decomposed into a group of ellipses, and the original shape contour can be re-constructed using the decomposed ellipses. The ellipse-based shape description and similar retrieval method is introduced in this paper. Based on ellipse's contribution to shape contour, the decomposed ellipses are parted into low-order ellipses and high-order ellipses. The low-order ellipses measure the macroscopic feature of a shape contour, and the high-order ellipses measure the microscopic feature. The two-phase shape matching method is given. Through the experiment test, our method has better shape retrieval effect.展开更多
文摘A large number of 3D models are created on computers and available for networks. Some content-based retrieval technologies are indispensable to find out particular data from such anonymous datasets. Though several shape retrieval technologies have been developed, little attention has been given to the points on human＇s sense and impression （as known as Kansei） in the conventional techniques, In this paper, the authors propose a novel method of shape retrieval based on shape impression of human＇s Kansei. The key to the method is the Gaussian curvature distribution from 3D models as features for shape retrieval. Then it classifies the 3D models by extracted feature and measures similarity among models in storage.
基金supported by the National Key R&D Plan of China(2016YFB1001501)
文摘We develop a data driven method(probability model) to construct a composite shape descriptor by combining a pair of scale-based shape descriptors. The selection of a pair of scale-based shape descriptors is modeled as the computation of the union of two events, i.e.,retrieving similar shapes by using a single scale-based shape descriptor. The pair of scale-based shape descriptors with the highest probability forms the composite shape descriptor. Given a shape database, the composite shape descriptors for the shapes constitute a planar point set.A VoR-Tree of the planar point set is then used as an indexing structure for efficient query operation. Experiments and comparisons show the effectiveness and efficiency of the proposed composite shape descriptor.
基金Supported by national 973 research project(G1998030500) and PhDs special researchproject (1999035808)
文摘By using the generalized Gaussian density model, this letter puts forward a new shape retrieval way based on the wavelet coefficients. Experimental results show that the proposed shape feature description is superior to the traditional invariant moment algorithm. Moreover, this algorithm provides the important invariant trait to image's size and rotation, which can retrieve images based on shape with more similar results comparing with invariant moment method.
文摘Artificial intelligence and computer vision need methods for 2D （two-dimensional） shape retrieval having discrete set of boundary points. A novel method of MHR （Hurwitz-Radon Matrices） is used in shape modeling. Proposed method is based on the family of MHR which possess columns composed of orthogonal vectors. 2D curve is retrieved via different functions as probability distribution functions： sine, cosine, tangent, logarithm, exponent, arcsin, arccos, arctan and power function. Created from the family of N-1 MHR and completed with the identical matrix, system of matrices is orthogonal only for dimensions N = 2, 4 or 8. Orthogonality of columns and rows is very significant for stability and high precision of calculations. MHR method is interpolating the function point by point without using any formula of function. Main features of MHR method are： accuracy of curve reconstruction depending on number of nodes and method of choosing nodes, interpolation of L points of the curve is connected with the computational cost of rank O（L）, MHR interpolation is not a linear interpolation.
文摘The matching and retrieval of the 2D shapes are challenging issues in object recognition and computer vision. In this paper, we propose a new object contour descriptor termed ECPDH (Elliptic Contour Points Distribution Histogram), which is based on the distribution of the points on an object contour under the polar coordinates. ECPDH has the essential merits of invariance to scale and translation. Dynamic Programming (DP) algorithm is used to measure the distance between the ECPDHs. The effectiveness of the proposed method is demonstrated using some standard tests on MPEG-7 shape database. The results show the precision and recall of our method over other recent methods in the literature.
基金the National Natural Science Foundation of China under Grant Nos.61872316,61932018.
文摘Feature analysis plays a significant role in computer vision and computer graphics.In the task of shape retrieval,shape descriptor is indispensable.In recent years,feature extraction based on deep learning becomes very popular,but the design of geometric shape descriptor is still meaningful due to the contained intrinsic information and interpretability.This paper proposes an effective and robust descriptor of 3D models.The descriptor is constructed based on the probability distribution of the normalized eigenfunctions of the Laplace–Beltrami operator on the surface,and a spectrum method for dimensionality reduction.The distance metric of the descriptor space is learned by utilizing the joint Bayesian model,and we introduce a matrix regularization in the training stage to re-estimate the covariance matrix.Finally,we apply the descriptor to 3D shape retrieval on a public benchmark.Experiments show that our method is robust and has good retrieval performance.
基金National Natural Science Foundation of China(No. 60172045)863-306 Project (863-306-ZT03-09)
文摘A method of shape encoding and retrieval is proposed in this letter, which uses centripetal code to encode shape and extracts shape's convex for retrieval. For the rotation invariance and translation invariance of the centripetal code and the normalization of convex,the proposed retrieval method is similarity transform resistant, Experimental results confirm this capability.
基金The Basic Research of COSTIND,China (No.D0420060521)
文摘To reuse and share the valuable knowledge embedded in repositories of engineering models for accelerating the design process, improving product quality, and reducing costs, it is crucial to devise search engines capable of matching 3D models efficiently and effectively. In this paper, an enhanced shape distributions-based technique of using geometrical and topological information to search 3D engineering models represented by polygonal meshes was presented. A simplification method of polygonal meshes was used to simplify engineering model as the pretreatment for generation of sample points. The method of sampling points was improved and a pair of functions that was more sensitive to shape was employed to construct a 2D shape distribution. Experiments were conducted to evaluate the proposed algorithm utilizing the Engineering Shape Benchmark (ESB) database. The experiential results suggest that the search effectiveness is significantly improved by enforcing the simplification and enhanced shape distributions to engineering model retrieval.
基金supported by National Science Foundation under Collaborative Research grants to Stony Brook University (Grant No. CMMI-0856594)University of Maryland at Baltimore County (Grant No. CMMI-0900517)supported by National Natural Science Foundation of China under Oversea Scholar Research Collaboration to Shanghai Jiao Tong University (Grant No. 50728503)
文摘Fourier Descriptors（FD） has been widely used in image analysis and computer vision for shape recognition as they can be made independent of translation,rotation,as well as scaling.They have also been used for developing methods for the analysis and synthesis of four-bar linkages for path generation.This paper focuses on a comparative study of Fourier descriptors derived from various shape signatures of planar closed curves.This includes representations based on Cartesian coordinates,centroid distance,cumulative angle,and curvature.The comparison is conducted not only using commonly used criteria for shape representation and identification but also in the context of shape based retrieval of kinematic constraints for task centered mechanism design.Examples are provided to seek to extract geometric constraints such as circle,circular arc,ellipse and line-segment from a given motion.
基金supported by the National Key R&D Program of China(2020YFB1708900)the National Natural Science Foundation of China(62072271).
文摘We propose a unified 3D flow frameworkfor joint learning of shape embedding and deformationfor different categories. Our goal is to recovershapes from imperfect point clouds by fitting thebest shape template in a shape repository afterdeformation. Accordingly, we learn a shape embeddingfor template retrieval and a flow-based network forrobust deformation. We note that the deformationflow can be quite different for different shapecategories. Therefore, we introduce a novel multi-hubmodule to learn multiple modes of deformation toincorporate such variation, providing a network whichcan handle a wide range of objects from differentcategories. The shape embedding is designed to retrievethe best-fit template as the nearest neighbor in a latentspace. We replace the standard fully connected layerwith a tiny structure in the embedding that significantlyreduces network complexity and further improvesdeformation quality. Experiments show the superiorityof our method to existing state-of-the-art methods viaqualitative and quantitative comparisons. Finally, ourmethod provides efficient and flexible deformation thatcan further be used for novel shape design.
文摘Using a group of ellipses to approach the shape contour, a new shape retrieval method is presented in this paper. In order to keep shape-based retrieval invariant to its position, orientation and size, the shape normalization method is presented. From our research, any closed shape contour can be uniquely decomposed into a group of ellipses, and the original shape contour can be re-constructed using the decomposed ellipses. The ellipse-based shape description and similar retrieval method is introduced in this paper. Based on ellipse's contribution to shape contour, the decomposed ellipses are parted into low-order ellipses and high-order ellipses. The low-order ellipses measure the macroscopic feature of a shape contour, and the high-order ellipses measure the microscopic feature. The two-phase shape matching method is given. Through the experiment test, our method has better shape retrieval effect.
