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Chapter 5: Smooth Surface Reconstruction Using Doo-Sabin Subdivision Surfaces 第五章:使用Doo-Sabin细分曲面进行光滑曲面重建
2008 3rd International Conference on Geometric Modeling and Imaging Pub Date : 2008-07-09 DOI: 10.1109/GMAI.2008.15
F. Cheng, Fengtao Fan, Conglin Huang, Jiaxi Wang, S. Lai, K. Miura
{"title":"Chapter 5: Smooth Surface Reconstruction Using Doo-Sabin Subdivision Surfaces","authors":"F. Cheng, Fengtao Fan, Conglin Huang, Jiaxi Wang, S. Lai, K. Miura","doi":"10.1109/GMAI.2008.15","DOIUrl":"https://doi.org/10.1109/GMAI.2008.15","url":null,"abstract":"A new technique for the reconstruction of a smooth surface from a set of 3D data points is presented. The reconstructed surface is represented by an everywhere C1-continuous subdivision surface which interpolates all the given data points. The new technique consists of two major steps. First, an efficient surface reconstruction method is applied to produce a polyhedral approximation to the given data set M. A Doo-Sabin subdivision surface that smoothly passes through all the points in the given data set M is then constructed. The Doo-Sabin subdivision surface is constructed by iteratively modifying the vertices of the polyhedral approximation until a new control mesh Mmacr, whose Doo-Sabin subdivision surface interpolates M, is reached. This iterative process converges for meshes of any size and any topology. Therefore the surface reconstruction processes well-defined. The new technique has the advantages of both a local method and a global method, and the surface reconstruction process can reproduce special features such as edges and corners faithfully.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129054280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Fuzzy Decision Maker for Knowledge Discovery from Image Archives 图像档案知识发现的模糊决策方法
2008 3rd International Conference on Geometric Modeling and Imaging Pub Date : 2008-07-09 DOI: 10.1109/GMAI.2008.12
F. Safara, S. Naderi
{"title":"Fuzzy Decision Maker for Knowledge Discovery from Image Archives","authors":"F. Safara, S. Naderi","doi":"10.1109/GMAI.2008.12","DOIUrl":"https://doi.org/10.1109/GMAI.2008.12","url":null,"abstract":"With this enormous speed in generating and collecting images, there is an extreme need in extracting interesting and useful knowledge from image archives. In our previous works, we have proposed an image mining framework to extract knowledge from a sequence of images. The framework is composed of two main modules: image analysis and knowledge processing. In this paper, we successfully customized the knowledge processing module to check legality/normality of vehicles/people behaviors in different image sequences by means of a fuzzy decision maker (FDM).","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"30 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120858085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Chapter 4: Simulating a Deformable Object Using a Surface Mass Spring System 第四章:用表面质量弹簧系统模拟可变形物体
2008 3rd International Conference on Geometric Modeling and Imaging Pub Date : 2008-07-09 DOI: 10.1109/GMAI.2008.24
S. Arnab, V. Raja
{"title":"Chapter 4: Simulating a Deformable Object Using a Surface Mass Spring System","authors":"S. Arnab, V. Raja","doi":"10.1109/GMAI.2008.24","DOIUrl":"https://doi.org/10.1109/GMAI.2008.24","url":null,"abstract":"This paper introduces volume springs that provide the volume effect to a surface model when it is deformed. The estimation of the properties of the model takes the real material properties into consideration, where each spring stiffness is derived based on the elasticity, rigidity and compressibility modulus. The proposed model can be adopted to simulate soft objects such as a deformable human breast, and it can be further extended to address other material properties.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134329970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Chapter 20: A Fingerprint Local-Matching Algorithm Using Unit-Circle Parametrization 第20章:基于单位圆参数化的指纹局部匹配算法
2008 3rd International Conference on Geometric Modeling and Imaging Pub Date : 2008-07-09 DOI: 10.1109/GMAI.2008.29
Nam-seok Choi, Joon-Jae Lee, Byung-Gook Lee
{"title":"Chapter 20: A Fingerprint Local-Matching Algorithm Using Unit-Circle Parametrization","authors":"Nam-seok Choi, Joon-Jae Lee, Byung-Gook Lee","doi":"10.1109/GMAI.2008.29","DOIUrl":"https://doi.org/10.1109/GMAI.2008.29","url":null,"abstract":"Pattern recognition provides solution to many problems in real life such as in biometric system, personal identification of banks etc. It matches two point sets and consequently identify if they are identical. This is applicable in fingerprint recognition with minutiae as a representation, which has been widely used as an individual identification method. Fingerprint recognition is divided into two parts. One is to extract feature points from fingerprint image, another is matching of point pattern. This paper presents a matching algorithm. The Wamelenpsilas approach, which finds k-nearest neighbors, is quite famous recently. But in this paper, we studied the application of Delaunay triangulation and parametrization. This method maps local neighborhood of points of two different point sets to a unit-circle. In this paper, we get topology information, which is the raw data, from feature point of real finger by using Delaunay triangulation method. In consisted topology structure, we call a linked convex polygon that includes an interior point as one-ring. The one-ring is mapped to a unit-circle using parametrization. In this paper, we use shape-preserving parametrization method. In local matching, each area of polygon in unit-circle is compared. If the difference of two areas are within tolerance, two polygons are consider to be matched and then translation, rotation and scaling factors for global matching are calculated.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129000216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Chapter 19: Hybrid Fingerprint Verification System Based on Fusion of Feature Extraction and Minutiae Detection Strategy 第十九章:基于特征提取与细节检测策略融合的混合指纹验证系统
2008 3rd International Conference on Geometric Modeling and Imaging Pub Date : 2008-07-09 DOI: 10.1109/GMAI.2008.19
F. Janjua, M. Y. Javed, N. Sarfraz
{"title":"Chapter 19: Hybrid Fingerprint Verification System Based on Fusion of Feature Extraction and Minutiae Detection Strategy","authors":"F. Janjua, M. Y. Javed, N. Sarfraz","doi":"10.1109/GMAI.2008.19","DOIUrl":"https://doi.org/10.1109/GMAI.2008.19","url":null,"abstract":"In this Paper we have presented a Fingerprint verification system based on hybrid approach which combines both the Feature extraction by applying a set of different wavelet families (functions) and minutiae information available in the fingerprint image by fusion rule method. The Core Point (CP) of the input Fingerprint is detected. Keeping the CP in the center,the image of size w x w is cropped and further processing is done with the cropped portion of the image. The cropped portion of the image is divided into four equal parts and each part is decomposed into frequency sub-bands for feature extraction. Minutiae are also detected from the cropped portion of the image. To evaluate the systempsilas rate of FAR and FRR, the DET curve has been implemented which will automatically plot the graph between FAR and FRR of the proposed system. Extensive experiments have been conducted on FVC2002 and Biometric System Lab fingerprint database. The results of this hybrid technique have also been compared by replacing the proposed approach with Gabor filter convolution strategy for feature extraction with 16 Gabor filters. The performance output shows the tremendous efficacy of the proposed system.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126368014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Chapter 7: A Vector Representation for Polyhedra 第七章:多面体的向量表示
2008 3rd International Conference on Geometric Modeling and Imaging Pub Date : 2008-07-09 DOI: 10.1109/GMAI.2008.17
M. Rosenman, R. Stouffs
{"title":"Chapter 7: A Vector Representation for Polyhedra","authors":"M. Rosenman, R. Stouffs","doi":"10.1109/GMAI.2008.17","DOIUrl":"https://doi.org/10.1109/GMAI.2008.17","url":null,"abstract":"This paper presents a vector representation for polyhedra. Unlike coordinate representations, vector representations do not require fixing the polyhedra in a coordinate space to derive various properties or carry out various processes. The paper shows how the representation of primitive polyhedra can be used in a cellular construction of complex polyhedra through the gluing of counteractive faces. Counteractive faces are faces which have equal but opposite vector loops.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123145714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Chapter 12: Contour Rectification and Analysis Using Circular Augmented Rotational Trajectory Algorithm 第十二章:基于圆增广旋转轨迹算法的轮廓校正与分析
2008 3rd International Conference on Geometric Modeling and Imaging Pub Date : 2008-07-09 DOI: 10.1109/GMAI.2008.10
Russel A. Apu, M. Gavrilova
{"title":"Chapter 12: Contour Rectification and Analysis Using Circular Augmented Rotational Trajectory Algorithm","authors":"Russel A. Apu, M. Gavrilova","doi":"10.1109/GMAI.2008.10","DOIUrl":"https://doi.org/10.1109/GMAI.2008.10","url":null,"abstract":"This paper presents a novel circular augmented rotational trajectory (CART) algorithm to compute an R-space based shape descriptors which allow efficient shape matching, generalization and classification. The rotation invariant R-space representation can be used to detect invariant geometric features despite the presence of considerable noise and quantization errors. Moreover, the CART method is corner preserving and can detect the points of discontinuity in a noisy trajectory. Experimental analysis performed on a number of difficult or ambiguous object boundaries show that the CART method can correctly detect and represent the inherent shape and extract their geometric properties. The method's universality, robustness and consistent performance on a variety of difficult shapes make it a power technique for contour representation and analysis.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130548689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Chapter 18: Sub-tensor Decomposition for Expression Variant 3D Faces Recognition 第十八章:基于子张量分解的表情变体三维人脸识别
2008 3rd International Conference on Geometric Modeling and Imaging Pub Date : 2008-07-09 DOI: 10.1109/GMAI.2008.25
Jacey-Lynn Minoi, D. Gillies
{"title":"Chapter 18: Sub-tensor Decomposition for Expression Variant 3D Faces Recognition","authors":"Jacey-Lynn Minoi, D. Gillies","doi":"10.1109/GMAI.2008.25","DOIUrl":"https://doi.org/10.1109/GMAI.2008.25","url":null,"abstract":"We have investigated a technique for recognising faces invariant of facial expressions. We apply multi-linear tensor algebra, which subsumes linear algebra, to analyse and recognise 3D face surfaces. This potent framework possesses a remarkable ability to deal with the shortcomings of principle component analysis in less constrained situations. A set of vector spaces can be used to represent the variation of collections of face models with multiple formation factors across various modes, without destroying the detail of each other. Using multi-linear single value decomposition (SVD) yields better recognition rates than principal component analysis. We have used a set of landmarks as the input data for our multi-linear SVD recognition experiments. Our results have shown that the choice of landmarks may contribute to the accuracy of recognition. We have used the face action coding system (FACS) framework for manual selection of landmarks on prominent facial features as well as on muscle areas.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130235462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Chapter 3: The Sign Corrected Midpoint Decision Variable Selects the Candidate Point with the Minimum Euclidean Distance to the Conic 第三章:正号修正中点决策变量选取到二次曲线的欧氏距离最小的候选点
2008 3rd International Conference on Geometric Modeling and Imaging Pub Date : 2008-07-09 DOI: 10.1109/GMAI.2008.8
V. Huypens
{"title":"Chapter 3: The Sign Corrected Midpoint Decision Variable Selects the Candidate Point with the Minimum Euclidean Distance to the Conic","authors":"V. Huypens","doi":"10.1109/GMAI.2008.8","DOIUrl":"https://doi.org/10.1109/GMAI.2008.8","url":null,"abstract":"You can expect many new things: 1. An efficient 8-connected algorithm calculating the minimum Euclidean distance to the conic. 2. Bounding the Euclidean distance with the arithmetic mean and midpoint decision variable. 3. Highlighting the out-of-tolerance cases and the formulation of a solution. 4. Restore the renounced two-point decision variable(s). 5. Clear up the midpoint decision variable, by introducing the polar-line of the conic.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128584970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Chapter 14: A Comparative Study of ICA Based Approaches for Separation of Components in Functional MRI Sequences 第14章:基于ICA的功能MRI序列组分分离方法的比较研究
2008 3rd International Conference on Geometric Modeling and Imaging Pub Date : 2008-07-09 DOI: 10.1109/GMAI.2008.9
G.R. Rad, H. Larijani
{"title":"Chapter 14: A Comparative Study of ICA Based Approaches for Separation of Components in Functional MRI Sequences","authors":"G.R. Rad, H. Larijani","doi":"10.1109/GMAI.2008.9","DOIUrl":"https://doi.org/10.1109/GMAI.2008.9","url":null,"abstract":"This paper prepares a review of ICA based approaches that are used for separation of components in functional MRI sequences. In previous works, the FastICA and the Infomax algorithms are investigated in more details; therefore, in this paper we focus on methods such as \"radical ICA\", \"SDD ICA\", \"Erica\" and \"Evd\" for separation purposes. This comparative study provides reliable framework for brain researchers to choose appropriate ICA based method for their special investigation purposes.","PeriodicalId":393559,"journal":{"name":"2008 3rd International Conference on Geometric Modeling and Imaging","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123251489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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