Hierarchical Support Vector Regression

In the previous chapter the RBFN model and the advantages of a hierarchical version for surface reconstruction has been presented. In a similar way in this chapter another paradigm, Support Vector Regression (SVR), and its hierarchical version, Hierarchical Support Vector Regression (HSVR) that allows an efficient construction of the approximating surface, are introduced. Thanks to the hierarchical structure, the model can be better applied to 3D surface reconstruction giving a new, more robust and faster configuration procedure.

[1]  Tu Bao Ho,et al.  An efficient method for simplifying support vector machines , 2005, ICML.

[2]  C. G. Broyden.  The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations , 1970 .

[3]  Frédéric Truchetet,et al.  Boolean operations with implicit and parametric representation of primitives using R-functions , 2005, IEEE Transactions on Visualization and Computer Graphics.

[4]  Wim Sweldens,et al.  The lifting scheme: a construction of second generation wavelets , 1998 .

[5]  Naga K. Govindaraju,et al.  A Survey of General‐Purpose Computation on Graphics Hardware , 2007 .

[6]  N. Alberto Borghese,et al.  Hierarchical RBF networks and local parameters estimate , 1998, Neurocomputing.

[7]  David R. Forsey,et al.  Multiresolution Surface Reconstruction for Hierarchical B-splines , 1998, Graphics Interface.

[8]  Peter Dayan,et al.  Technical Note: Q-Learning , 2004, Machine Learning.

[9]  David R. Forsey,et al.  Hierarchical B-spline refinement , 1988, SIGGRAPH.

[10]  Giancarlo Ferrigno,et al.  Reducing and Filtering Point Clouds With Enhanced Vector Quantization , 2007, IEEE Transactions on Neural Networks.

[11]  Iuri Frosio,et al.  Optimized algebraic local tomogragphy , 2010 .

[12]  Lingrui Dai,et al.  The 3D Digital Technology of Fashion Design , 2011, 2011 International Symposium on Computer Science and Society.

[13]  Steven Skiena,et al.  Optimizing triangle strips for fast rendering , 1996, Proceedings of Seventh Annual IEEE Visualization '96.

[14]  Bin Xue,et al.  Real‐value prediction of backbone torsion angles , 2008, Proteins.

[15]  Gerd Hirzinger,et al.  A self-organizing algorithm for multisensory surface reconstruction , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[16]  Greg Humphreys,et al.  How GPUs Work , 2007, Computer.

[17]  Francesco Soldovieri,et al.  A Tomographic Approach for Helicopter-Borne Ground Penetrating Radar Imaging , 2012, IEEE Geoscience and Remote Sensing Letters.

[18]  Iuri Frosio,et al.  Linear pose estimate from corresponding conics , 2012, Pattern Recognit..

[19]  C. N. Canagarajah,et al.  Image fusion using a 3-D wavelet transform , 1999 .

[20]  Songcan Chen,et al.  MultiK-MHKS: A Novel Multiple Kernel Learning Algorithm , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  Sholom M. Weiss,et al.  Optimized rule induction , 1993, IEEE Expert.

[22]  Giancarlo Ferrigno,et al.  AUTOSCAN: A flexible and portable scanner of 3D surfaces , 1998 .

[23]  F. Girosi,et al.  Networks for approximation and learning , 1990, Proc. IEEE.

[24]  G. Wahba.  Smoothing noisy data with spline functions , 1975 .

[25]  E. Catmull,et al.  Recursively generated B-spline surfaces on arbitrary topological meshes , 1978 .

[27]  Xiao Fu,et al.  Online Support Vector Regression for System Identification , 2005, ICNC.

[28]  Christian Whler.  3D Computer Vision: Efficient Methods and Applications , 2009 .

[29]  Roberto Cipolla,et al.  Multiview Photometric Stereo , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[30]  Vincenzo Piuri,et al.  Multi-resolution models for data processing: an experimental sensitivity analysis , 2000, Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference [Cat. No. 00CH37066].

[31]  Narciso García,et al.  Hierarchical coding of 3D models with subdivision surfaces , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[32]  N. Alberto Borghese,et al.  Computing camera focal length by zooming a single point , 2006, Pattern Recognit..

[33]  Bernd Fritzke.  Growing Grid — a self-organizing network with constant neighborhood range and adaptation strength , 1995, Neural Processing Letters.

[34]  Robert M. O'Bara,et al.  Geometrically deformed models: a method for extracting closed geometric models form volume data , 1991, SIGGRAPH.

[35]  Vincenzo Piuri,et al.  A Hierarchical RBF Online Learning Algorithm for Real-Time 3-D Scanner , 2010, IEEE Transactions on Neural Networks.

[36]  Gang Wang,et al.  Registration and Integration of Multiple Object Views for 3D Model Construction , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[37]  John D. Owens,et al.  GPU Computing , 2008, Proceedings of the IEEE.

[38]  W. Dorn.  Duality in Quadratic Programming... , 2011 .

[39]  Wim Sweldens,et al.  Lifting scheme: a new philosophy in biorthogonal wavelet constructions , 1995, Optics + Photonics.

[40]  H. Altay Güvenir,et al.  An overview of regression techniques for knowledge discovery , 1999, The Knowledge Engineering Review.

[41]  Peter Craven,et al.  Smoothing noisy data with spline functions , 1978 .

[42]  Haralambos Sarimveis,et al.  A new algorithm for online structure and parameter adaptation of RBF networks , 2003, Neural Networks.

[43]  Trevor Hastie,et al.  Automatic Smoothing Spline Projection Pursuit , 1994 .

[44]  Peisen S. Huang,et al.  Fast three-step phase-shifting algorithm , 2006 .

[45]  Jarek Rossignac,et al.  Edgebreaker: Connectivity Compression for Triangle Meshes , 1999, IEEE Trans. Vis. Comput. Graph..

[46]  Stephen A. Billings,et al.  Radial basis function network configuration using genetic algorithms , 1995, Neural Networks.

[47]  Marzuki Khalid,et al.  A Non-linear Function Approximation from Small Samples Based on Nadaraya-Watson Kernel Regression , 2010, 2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks.

[48]  Giancarlo Ferrigno,et al.  Autoscan: A Flexible and Portable 3D Scanner , 1998, IEEE Computer Graphics and Applications.

[49]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[50]  Mark J. L. Orr,et al.  Regularization in the Selection of Radial Basis Function Centers , 1995, Neural Computation.

[51]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.

[52]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[53]  Dong Wang,et al.  Two heuristic strategies for searching optimal hyper parameters of C-SVM , 2009, 2009 International Conference on Machine Learning and Cybernetics.

[54]  Heinrich Müller,et al.  Interpolation and Approximation of Surfaces from Three-Dimensional Scattered Data Points , 1997, Scientific Visualization Conference (dagstuhl '97).

[55]  Tony DeRose,et al.  Surface reconstruction from unorganized points , 1992, SIGGRAPH.

[56]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[57]  Kurt Keutzer,et al.  Fast support vector machine training and classification on graphics processors , 2008, ICML '08.

[58]  Peter J. Rousseeuw,et al.  Finding Groups in Data: An Introduction to Cluster Analysis , 1990 .

[59]  I. Kassamakov,et al.  Scanning White Light Interferometry, — A new 3D forensics tool , 2011, 2011 IEEE International Conference on Technologies for Homeland Security (HST).

[60]  Joaquim Salvi,et al.  Recent progress in coded structured light as a technique to solve the correspondence problem: a survey , 1998, Pattern Recognit..

[61]  J. Friedman.  Multivariate adaptive regression splines , 1990 .

[62]  Adam Finkelstein,et al.  Robust mesh watermarking , 1999, SIGGRAPH.

[63]  R. Palmer,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.

[64]  Alessandro Rozza,et al.  IDEA: Intrinsic Dimension Estimation Algorithm , 2011, ICIAP.

[65]  G. Olhoeft.  Applications and frustrations in using ground penetrating radar , 2002 .

[66]  Hongbin Zha,et al.  A Recursive Fitting-and-Splitting Algorithm for 3-D Object Modeling Based on Superquadrics , 1998, ACCV.

[67]  Byron Perez-Gutierrez,et al.  Endoscopic endonasal haptic surgery simulator prototype: A rigid endoscope model , 2010, 2010 IEEE Virtual Reality Conference (VR).

[68]  E. De Momi,et al.  An intelligent atlas-based planning system for keyhole neurosurgery , 2009 .

[69]  Gérard Dreyfus,et al.  Neural networks - methodology and applications , 2005 .

[70]  Bedri C. Cetin,et al.  Terminal repeller unconstrained subenergy tunneling (trust) for fast global optimization , 1993 .

[71]  Yue Qi,et al.  3D Modeling, Codec and Protection in Digital Museum , 2007, Second Workshop on Digital Media and its Application in Museum & Heritages (DMAMH 2007).

[72]  Stefano Ferrari,et al.  3D Scanner, State of the Art , 2012 .

[73]  B. Schölkopf,et al.  Asymptotically Optimal Choice of ε-Loss for Support Vector Machines , 1998 .

[74]  Yuqing Chen,et al.  A novel 3D surface modeling based on Spatial Neighbor Points Coupling in reverse engineering , 2010, 2010 International Conference On Computer Design and Applications.

[75]  Ruigang Yang,et al.  Registering, integrating, and building CAD models from range data , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[76]  David W. Aha,et al.  Instance-Based Learning Algorithms , 1991, Machine Learning.

[77]  Denise Gorse,et al.  Avoiding Local Minima by a Classical Range Expansion Algorithm , 1994 .

[78]  F. Canal,et al.  An optical 3D digitizer for industrial quality control applications , 1999, 1999 7th IEEE International Conference on Emerging Technologies and Factory Automation. Proceedings ETFA '99 (Cat. No.99TH8467).

[79]  Lu Wang,et al.  3D building reconstruction from LiDAR data , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[80]  Marek Teichmann,et al.  Surface reconstruction with anisotropic density-scaled alpha shapes , 1998 .

[81]  Frédo Durand,et al.  Image and depth from a conventional camera with a coded aperture , 2007, SIGGRAPH 2007.

[82]  Michael Garland,et al.  Optimal triangulation and quadric-based surface simplification , 1999, Comput. Geom..

[83]  David P. Dobkin,et al.  MAPS: multiresolution adaptive parameterization of surfaces , 1998, SIGGRAPH.

[84]  Michael Potmesil.  Generating octree models of 3D objects from their silhouettes in a sequence of images , 1987, Comput. Vis. Graph. Image Process..

[85]  Vincenzo Piuri,et al.  Hierarchical Approach for Multiscale Support Vector Regression , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[86]  Sung Yong Shin,et al.  Scattered Data Interpolation with Multilevel B-Splines , 1997, IEEE Trans. Vis. Comput. Graph..

[87]  Wei-Yin Loh,et al.  Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..

[88]  Bernhard Schölkopf,et al.  Incorporating Invariances in Support Vector Learning Machines , 1996, ICANN.

[89]  Bernhard Schölkopf,et al.  Extracting Support Data for a Given Task , 1995, KDD.

[90]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[91]  Marc Levoy,et al.  Real-time 3D model acquisition , 2002, ACM Trans. Graph..

[92]  Alberto Del Bimbo,et al.  Metric 3D reconstruction and texture acquisition of surfaces of revolution from a single uncalibrated view , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[93]  Nada Lavrac,et al.  The Multi-Purpose Incremental Learning System AQ15 and Its Testing Application to Three Medical Domains , 1986, AAAI.

[94]  Claus Bahlmann,et al.  Online handwriting recognition with support vector machines - a kernel approach , 2002, Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition.

[95]  Vincenzo Piuri,et al.  Multi-scale Support Vector Regression , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[96]  Ji Zhao,et al.  Development of a Robotic 3D Scanning System for Reverse Engineering of Freeform Part , 2008, 2008 International Conference on Advanced Computer Theory and Engineering.

[97]  Vincenzo Piuri,et al.  Automatic multiscale meshing through HRBF networks , 2005, IEEE Transactions on Instrumentation and Measurement.

[98]  Zongwu Cai,et al.  Weighted Nadaraya–Watson regression estimation , 2001 .

[99]  Werner Jüptner,et al.  Digital recording and numerical reconstruction of holograms , 2002 .

[100]  D. Marquardt.  An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[101]  Kari Pulli,et al.  Multiview registration for large data sets , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[102]  John Moody,et al.  Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.

[103]  Francis Schmitt,et al.  Surface Reconstruction from Unstructured 3D Data , 1996, Comput. Graph. Forum.

[104]  Stephane Ruel,et al.  TriDAR: A HYBRID SENSOR FOR EXPLOITING THE COMPLEMENTARY NATURE OF TRIANGULATION AND LIDAR TECHNOLOGIES , 2005 .

[105]  N. Alberto Borghese,et al.  A portable modular system for automatic acquisition of 3D objects , 2000, IEEE Trans. Instrum. Meas..

[106]  Sheng Chen,et al.  Sparse kernel density construction using orthogonal forward regression with leave-one-out test score and local regularization , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[107]  Berthold K. P. Horn.  Obtaining shape from shading information , 1989 .

[108]  P. Hall.  On Projection Pursuit Regression , 1989 .

[109]  Vincenzo Piuri,et al.  A methodology for surface reconstruction based on hierarchical models , 2003, The 2nd IEEE Internatioal Workshop on Haptic, Audio and Visual Environments and Their Applications, 2003. HAVE 2003. Proceedings..

[110]  Anath Fischer,et al.  Parameterization and Reconstruction from 3D Scattered Points Based on Neural Network and PDE Techniques , 2001, IEEE Trans. Vis. Comput. Graph..

[111]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[112]  Ali Adnan Al-Temeemy.  Three dimensional LADAR imaging system using AR-4000LV laser rangefinder , 2011, 2011 MICROWAVES, RADAR AND REMOTE SENSING SYMPOSIUM.

[113]  David P. Dobkin,et al.  Multiresolution mesh morphing , 1999, SIGGRAPH.

[114]  Peter Schröder,et al.  Spherical wavelets: efficiently representing functions on the sphere , 1995, SIGGRAPH.

[115]  Gunnar Rätsch,et al.  Predicting Time Series with Support Vector Machines , 1997, ICANN.

[116]  Y. Katznelson.  An Introduction to Harmonic Analysis: Interpolation of Linear Operators , 1968 .

[117]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[118]  Peter Clark,et al.  The CN2 Induction Algorithm , 1989, Machine Learning.

[119]  Lakhmi C. Jain,et al.  New Learning Paradigms in Soft Computing , 2002 .

[120]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[121]  S. Sathiya Keerthi,et al.  Building Support Vector Machines with Reduced Classifier Complexity , 2006, J. Mach. Learn. Res..

[122]  Pietro Cerveri,et al.  Calibration of TV cameras through RBF networks , 1997, Optics & Photonics.

[123]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[124]  Hugues Hoppe,et al.  Displaced subdivision surfaces , 2000, SIGGRAPH.

[125]  Jin Hyeong Park,et al.  Multi-resolution boosting for classification and regression problems , 2009, Knowledge and Information Systems.

[126]  E.I. Perez,et al.  Evaluation of 3D Scanners to Develop Virtual Reality Applications , 2007, Electronics, Robotics and Automotive Mechanics Conference (CERMA 2007).

[127]  Marc Levoy,et al.  Zippered polygon meshes from range images , 1994, SIGGRAPH.

[128]  Zhu Bo,et al.  GA Based Redundant Ring Topology Optimization of Industrial WLAN , 2007, Second Workshop on Digital Media and its Application in Museum & Heritages (DMAMH 2007).

[129]  Kumpati S. Narendra,et al.  Gradient methods for the optimization of dynamical systems containing neural networks , 1991, IEEE Trans. Neural Networks.

[130]  Bernhard Schölkopf,et al.  A tutorial on support vector regression , 2004, Stat. Comput..

[131]  Namho Hur,et al.  3DTV Broadcasting and Distribution Systems , 2011, IEEE Transactions on Broadcasting.

[132]  David J. Kriegman,et al.  The Bas-Relief Ambiguity , 2004, International Journal of Computer Vision.

[133]  Domenico Visintini,et al.  The VRML model of Victoria Square in Gorizia (Italy) from laser scanning and photogrammetric 3D surveys , 2007, Web3D '07.

[134]  Belur V. Dasarathy,et al.  Nearest neighbor (NN) norms: NN pattern classification techniques , 1991 .

[135]  John C. Platt.  A Resource-Allocating Network for Function Interpolation , 1991, Neural Computation.

[136]  G. Walter,et al.  Remarks on projection pursuit regression and density estimation , 1992 .

[137]  Shun-ichi Amari,et al.  A Theory of Pattern Recognition , 1968 .

[138]  Olivier D. Faugeras,et al.  Using Extremal Boundaries for 3-D Object Modeling , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[139]  W. Sweldens.  The Lifting Scheme: A Custom - Design Construction of Biorthogonal Wavelets "Industrial Mathematics , 1996 .

[140]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[141]  Adrião Duarte Dória Neto,et al.  An Adaptive Learning Approach for 3-D Surface Reconstruction From Point Clouds , 2008, IEEE Trans. Neural Networks.

[142]  Jongmoo Choi,et al.  Non-Cooperative Persons Identification at a Distance with 3D Face Modeling , 2007, 2007 First IEEE International Conference on Biometrics: Theory, Applications, and Systems.

[143]  Richard Levy,et al.  Reconstructing a thule whalebone house using 3D imaging , 2006, IEEE Multimedia.

[144]  Andrew W. Moore,et al.  Locally Weighted Learning , 1997, Artificial Intelligence Review.

[145]  Herbert Edelsbrunner,et al.  Three-dimensional alpha shapes , 1994, ACM Trans. Graph..

[146]  Jitendra Malik,et al.  Scale-Space and Edge Detection Using Anisotropic Diffusion , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[147]  Bowen Alpern,et al.  The hyperbox , 1991, Proceeding Visualization '91.

[148]  Elie Bienenstock,et al.  Neural Networks and the Bias/Variance Dilemma , 1992, Neural Computation.

[149]  Luis Pastor,et al.  Surface approximation of 3D objects from irregularly sampled clouds of 3D points using spherical wavelets , 1999, Proceedings 10th International Conference on Image Analysis and Processing.

[150]  Norberto M. Grzywacz,et al.  A computational theory for the perception of coherent visual motion , 1988, Nature.

[151]  Thomas Martinetz,et al.  'Neural-gas' network for vector quantization and its application to time-series prediction , 1993, IEEE Trans. Neural Networks.

[152]  Ivor W. Tsang,et al.  Core Vector Machines: Fast SVM Training on Very Large Data Sets , 2005, J. Mach. Learn. Res..

[153]  Michael J. Brooks.  Two Results Concerning Ambiguity in Shape From Shading , 1983, AAAI.

[154]  L. Feldkamp,et al.  Practical cone-beam algorithm , 1984 .

[155]  Robert J. Woodham,et al.  Photometric method for determining surface orientation from multiple images , 1980 .

[156]  Mark H. Lee,et al.  Error-driven active learning in growing radial basis function networks for early robot learning , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[157]  Kurt Hornik,et al.  Approximation capabilities of multilayer feedforward networks , 1991, Neural Networks.

[158]  Jitendra Malik,et al.  Modeling and Rendering Architecture from Photographs: A hybrid geometry- and image-based approach , 1996, SIGGRAPH.

[159]  O. Baltag,et al.  3D Breast Shape Reconstruction for a Non-Invasive Early Cancer Diagnosis System , 2007, 2007 2nd International Workshop on Soft Computing Applications.

[160]  I. Daubechies.  Orthonormal bases of compactly supported wavelets , 1988 .

[161]  Pier Luca Lanzi,et al.  Self-adaptive games for rehabilitation at home , 2012, 2012 IEEE Conference on Computational Intelligence and Games (CIG).

[162]  Sigbert Klinke,et al.  Projection pursuit regression and neural networks , 1998 .

[163]  Austin Carpenter,et al.  CUSVM: A CUDA IMPLEMENTATION OF SUPPORT VECTOR CLASSIFICATION AND REGRESSION , 2009 .

[164]  Les A. Piegl,et al.  The NURBS Book , 1995, Monographs in Visual Communication.

[165]  Alexander J. Smola,et al.  Support Vector Regression Machines , 1996, NIPS.

[166]  J. Friedman,et al.  Projection Pursuit Regression , 1981 .

[167]  Nello Cristianini,et al.  Learning the Kernel Matrix with Semidefinite Programming , 2002, J. Mach. Learn. Res..

[168]  J. Weston,et al.  Support vector regression with ANOVA decomposition kernels , 1999 .

[169]  G. Iddan,et al.  3D IMAGING IN THE STUDIO (AND ELSEWHERE...) , 2001 .

[170]  Wan-Chun Ma,et al.  The Digital Emily Project: Achieving a Photorealistic Digital Actor , 2010, IEEE Computer Graphics and Applications.

[171]  Torsten Kuhlen,et al.  Haptic Palpation for Medical Simulation in Virtual Environments , 2012, IEEE Transactions on Visualization and Computer Graphics.

[172]  Vincenzo Piuri,et al.  Online training of Hierarchical RBF , 2007, 2007 International Joint Conference on Neural Networks.

[173]  Jun'ichiro Seyama,et al.  The Uncanny Valley: Effect of Realism on the Impression of Artificial Human Faces , 2007, PRESENCE: Teleoperators and Virtual Environments.

[174]  D. M. Etter,et al.  Wavelet basis reconstruction of nonuniformly sampled data , 1998 .

[175]  Jindong Chen,et al.  Automatic Reconstruction of 3D CAD Models from Digital Scans , 1999, Int. J. Comput. Geom. Appl..

[176]  Chandrajit L. Bajaj,et al.  Automatic reconstruction of surfaces and scalar fields from 3D scans , 1995, SIGGRAPH.

[177]  Raffaella Fontana,et al.  A 3D scanning device for architectural survey based on time-of-flight technology , 2004, SPIE Photonics Europe.

[178]  T Yatagai,et al.  Scanning moiré method and automatic measurement of 3-D shapes. , 1977, Applied optics.

[179]  Sang Uk Lee,et al.  Automatic 3-D model synthesis from measured range data , 2000, IEEE Trans. Circuits Syst. Video Technol..

[180]  Pietro Cerveri,et al.  Calibrating a video camera pair with a rigid bar , 2000, Pattern Recognit..

[181]  David W. Aha,et al.  Instance‐based prediction of real‐valued attributes , 1989, Comput. Intell..

[182]  Stefan Rüping,et al.  Incremental Learning with Support Vector Machines , 2001, ICDM.

[183]  Ruzena Bajcsy,et al.  Building a 3D Virtual Museum of Native American Baskets , 2006, Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06).

[184]  Chun Chen,et al.  Sparse Coding for Flexible, Robust 3D Facial-Expression Synthesis , 2012, IEEE Computer Graphics and Applications.

[185]  Donald F. Specht,et al.  Probabilistic neural networks , 1990, Neural Networks.

[186]  Fengfeng Zhang,et al.  A new novel virtual simulation system for robot-assisted orthopedic surgery , 2007, 2007 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[187]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[188]  Rüdiger Westermann,et al.  Distance Visualization for Interactive 3D Implant Planning , 2011, IEEE Transactions on Visualization and Computer Graphics.

[189]  Tom Drummond,et al.  Rapid 3D modelling from live video , 2010, The 33rd International Convention MIPRO.

[190]  Patrick Henry Winston,et al.  The psychology of computer vision , 1976, Pattern Recognit..

[191]  Kenneth Levenberg.  A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .

[192]  G. Ferrigno,et al.  An algorithm for 3-D automatic movement detection by means of standard TV cameras , 1990, IEEE Transactions on Biomedical Engineering.

[193]  Vincenzo Piuri,et al.  Real-time surface meshing through HRBF networks , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[194]  P. Harman,et al.  Home based 3D entertainment-an overview , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[195]  Mauro Maggioni,et al.  Multiscale approximation with hierarchical radial basis functions networks , 2004, IEEE Transactions on Neural Networks.

[196]  V. Vapnik.  Pattern recognition using generalized portrait method , 1963 .

[197]  Ali A. Al-Temeemy,et al.  Three-dimensional ladar imaging system using AR-4000LV laser range-finder , 2011, Optical Systems Design.

[198]  James Theiler,et al.  Accurate On-line Support Vector Regression , 2003, Neural Computation.

[199]  Nadia Magnenat-Thalmann,et al.  Made-to-Measure Technologies for an Online Clothing Store , 2003, IEEE Computer Graphics and Applications.

[200]  Jean-Daniel Boissonnat,et al.  Geometric structures for three-dimensional shape representation , 1984, TOGS.

[201]  Dimitris N. Metaxas,et al.  Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[202]  Marc Levoy,et al.  The digital Michelangelo project: 3D scanning of large statues , 2000, SIGGRAPH.

[203]  Kumpati S. Narendra,et al.  Learning automata - an introduction , 1989 .

[204]  Dimitri P. Bertsekas,et al.  Nonlinear Programming , 1997 .

[205]  Vincenzo Piuri,et al.  Multiscale models for data processing: an experimental sensitivity analysis , 2001, IEEE Trans. Instrum. Meas..

[206]  Shin-Tseng Lee,et al.  A Remote Virtual-Surgery Training and Teaching System , 2007, 2007 3DTV Conference.

[207]  Gerhard Roth,et al.  An Efficient Volumetric Method for Building Closed Triangular Meshes from 3-D Image and Point Data , 1997, Graphics Interface.

[208]  David W. Capson,et al.  Surface profile measurement using color fringe projection , 1991, Machine Vision and Applications.

[209]  Tomaso A. Poggio,et al.  Regularization Theory and Neural Networks Architectures , 1995, Neural Computation.

[210]  Thorsten Joachims,et al.  Making large scale SVM learning practical , 1998 .

[211]  Yaohua Tang,et al.  Efficient model selection for Support Vector Machine with Gaussian kernel function , 2009, 2009 IEEE Symposium on Computational Intelligence and Data Mining.

[212]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[213]  J.I. Mulero-Martinez,et al.  Best Approximation of Gaussian Neural Networks With Nodes Uniformly Spaced , 2008, IEEE Transactions on Neural Networks.

[214]  Alexander J. Smola,et al.  Minimal Kernel Classifiers , 2002, J. Mach. Learn. Res..

[215]  Giovanna Sansoni,et al.  3-D optical measurements in the field of cultural heritage: the case of the Vittoria Alata of Brescia , 2005, IEEE Transactions on Instrumentation and Measurement.

[216]  Marjorie Skubic,et al.  Evaluation of an inexpensive depth camera for passive in-home fall risk assessment , 2011, 2011 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops.

[217]  Giancarlo Ferrigno,et al.  Portable and accurate 3D scanner for breast implant design and reconstructive plastic surgery , 1998, Medical Imaging.

[218]  D. Broomhead,et al.  Radial Basis Functions, Multi-Variable Functional Interpolation and Adaptive Networks , 1988 .

[219]  Marie-Paule Cani,et al.  Automatic Reconstruction of Unstructured 3D Data: Combining a Medial Axis and Implicit Surfaces , 1995, Comput. Graph. Forum.

[220]  Chanjira Sinthanayothin,et al.  Computerized algorithm for 3D teeth segmentation , 2010, 2010 International Conference on Electronics and Information Engineering.

[221]  Xun Liang,et al.  An Effective Method of Pruning Support Vector Machine Classifiers , 2010, IEEE Transactions on Neural Networks.

[222]  Manfred Opper,et al.  Sparse Representation for Gaussian Process Models , 2000, NIPS.

[223]  Bernd Fritzke,et al.  Growing cell structures--A self-organizing network for unsupervised and supervised learning , 1994, Neural Networks.

[224]  Ron Kohavi,et al.  A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.

[225]  Zhengyou Zhang,et al.  Flexible camera calibration by viewing a plane from unknown orientations , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[226]  Sholom M. Weiss,et al.  Rule-based Machine Learning Methods for Functional Prediction , 1995, J. Artif. Intell. Res..

[227]  V. Piuri,et al.  Kernel regression in HRBF networks for surface reconstruction , 2008, 2008 IEEE International Workshop on Haptic Audio visual Environments and Games.

[228]  M. Hasenjäger,et al.  Active learning in neural networks , 2002 .

[229]  T. Poggio.  A theory of how the brain might work. , 1990, Cold Spring Harbor symposia on quantitative biology.

[230]  V. Piuri,et al.  The accuracy of the HRBF networks , 2004, Proceedings of the 21st IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.04CH37510).

[231]  Yasuyuki Matsushita,et al.  A hand-held photometric stereo camera for 3-D modeling , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[232]  Andrew W. Fitzgibbon,et al.  KinectFusion: Real-time dense surface mapping and tracking , 2011, 2011 10th IEEE International Symposium on Mixed and Augmented Reality.

[233]  Bernd A. Berg,et al.  Locating global minima in optimization problems by a random-cost approach , 1993, Nature.

[234]  Robert M. Sanner,et al.  Gaussian Networks for Direct Adaptive Control , 1991, 1991 American Control Conference.

[235]  V. Piuri,et al.  Refining Hierarchical Radial Basis Function Networks , 2007, 2007 IEEE International Workshop on Haptic, Audio and Visual Environments and Games.

[236]  Thomas Vetter,et al.  Face Recognition Based on Fitting a 3D Morphable Model , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[237]  Vijay K. Jain,et al.  3D reconstruction from a stereo pair without the knowledge of intrinsic or extrinsic parameters , 2001, Proceedings Second International Workshop on Digital and Computational Video.

[238]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[239]  T. Dodd,et al.  Online functional prediction for spatio-temporal systems using time-varying Radial Basis Function networks , 2010, 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010).

[240]  I. Johnstone,et al.  Ideal spatial adaptation by wavelet shrinkage , 1994 .