Research On3D Model Partial Matching And Retrieval Methods

With the technology of3D model and Internet technology continues to evolve,more and more3D software and3D model files are shared on internet, and3Dmodel technology applications are increasingly being used just like product design,3D online game, simulation assembly and virtual reality. Especially in recent years,3D printers making3D model has begun to spread to home users and enable userscan print3D models with3D printers. So the research and development of3D modelsearch engines to help business users, home users to quickly and accurately retrievethe desired3D model of their own, is one of the focus in recent years.The main contents of the dissertation are presented as follows:Based on statistical feature extraction algorithm, proposes a area distributionsbased method outlying with3D system. According to the method, first summary thetotal area and average area of the vertex of the3D model, then normalized the list ofthe area distributions list and Fourier transform the list; last get the final areadistributions list model, and map the search of the model to the compare of the areadistributions list. Experiments were conducted to the comparison of evaluate theproposed algorithm utilizing the Engineering Shape Benchmark (ESB) database.The experiential results show that the proposed technique effectively reflected thesimilarity among engineering models, and the match result of the model whichextremely similar was accurate and the retrieval performance was significantlyimproved compared to traditional shape distribution method.Propose a new3D CAD model retrieval method. Properties associated with thevertex will be extracted from3D model to be calculated into description operators.First, calculate the Gaussian curvature of vertices and translate it into the angle α, atthe same time, calculate angle β between the vector from vertex to center of massand normal vector of vertex. We use angel α and angel β to build a3D plane matrixgrid by splitting α and β with pi/16, define grid function O at each cell and its valueis the sum of distances from all vertices to center of masses, then a characteristicmatrix of model16×16is generated. Finally compute the similarity between twomodels by specific rules. Use matrix similarity to measure the similarity of the twomodels, so as to achieve similarity retrieval. Use the ESB library of PurdueUniversity and model library of Princeton University to carry out retrievalexperiment and the results show that the algorithm in the paper has higher retrievalaccuracy.Propose a new3D model retrieval method based on normal-angle histogram.The method firstly makes the pretreatment for3D model, and defines the calculation method of the normal at every vertex of the triangular mesh in3D model and theincluded angle among the triangular meshes. Then it classifies the triangular mesh inaccordance with the normal at three vertexes of the triangular mesh and the includedangle among the triangular meshes, and divides the triangular mesh into four typesas per the included angle whether acute angle or obtuse angle, constructs the shapedistribution curve for every type of triangular mesh collection, obtains the similarityof two shapes by comparison of four shape distribution curves of3D model, andaccordingly realizes the similarity retrieval of3D model. The test indicates that theretrieval accuracy rate and the retrieval efficiency of the algorithm are superior toother similar histogram algorithm.Propose a new3D model retrieval method based on normal-angle histogram.The method firstly makes the pretreatment for3D model, and defines the calculationmethod of the normal at every vertex of the triangular mesh in3D model and theincluded angle among the triangular meshes. Then it classifies the triangular mesh inaccordance with the normal at three vertexes of the triangular mesh and the includedangle among the triangular meshes, and divides the triangular mesh into four typesas per the included angle whether acute angle or obtuse angle, constructs the shapedistribution curve for every type of triangular mesh collection, obtains the similarityof two shapes by comparison of four shape distribution curves of3D model, andaccordingly realizes the similarity retrieval of3D model. The test indicates that theretrieval accuracy rate and the retrieval efficiency of the algorithm are superior toother similar histogram algorithm.In partial matching and retrieval, we have introduced a3D segmentationtechnique. The partial description based on the eigenfunction of theLaplace-Beltrami operator is an important way. A large number of eigenfunctionvalues of any point on the surface of the model form a eigenvector; based on thisvector, K-means clustering method will be used to query the model which is dividedinto several regions; for each region, based on the Hungarian method which is usedin the solving of optimal assignment problem, search a corresponding region in thecompared model, so that achieving the partial matching between the two models.To validate the algorithm mentioned previously, we design and implement a3Dmodel retrieval system. The model library of this system is Engineering ShapeBenchmark which provided by Purdue University. Serival retrieval method wereimplement include area distribution algorithm, method based on property of vertex,method based on Laplace-Beltrami operator and other methods. We use this systemto validate our algorithm, analysis retrieval results and improve our algorithm.