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Filling holes in 3d meshes using image restoration algorithms 4

Filling holes in 3D meshes using image restoration algorithm...

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4th international symposium on 3d data processing, visualization and transmission, 3dpvt 2008

作者： Salamanca, Santiago Merchán, Pilar Adán, Antonio Pérez, Emiliano Cerrada, Carlos E. de Ingenierías Industriales Universidad de Extremadura Avda. de Elvas s/n Badajoz Spain E. S. de Ingeniería Informática Universidad de Castilla la Mancha P. de la Universidad 4 Ciudad Real Spain E. T. S. de Ingeniería Informática Universidad Nacional de Educación a Distancia C/ Juan del Rosal 16 Madrid Spain

this work describes a method for filling holes in a 3d mesh based on 2d image restoration algorithms. Since these algorithms need an image as input, the first stage of the method concerns a 3d to 2d transformation. By projecting the 3d surface onto a squared plane, a 2d image is generated in such a way that the depth information is stored in each grid. the image restoration algorithms are applied to it. Once the image has been repaired, the inverse transformation 2d to 3d is performed and the repaired 3d surface recovered. To test the method, artificial holes have been generated on a set of 3d surfaces. the goodness of the results has been measured from the comparison between the 3d original surfaces and the 3d repaired ones. An evaluation with commercial software has been carried out to show the validity of the method. the image restoration algorithms have been applied to 3d cultural heritage modeling with good results. Specifically, sculptures of the collection from the National Museum of Roman Art in Spain have been reconstructed. © 2008 Georgia Institute of Technology.

关键词： three dimensional computer graphics

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Accurate camera calibration and correction using rigidity and radial alignment constraints 4

Accurate camera calibration and correction using rigidity an...

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4th international symposium on 3d data processing, visualization and transmission, 3dpvt 2008

作者： Liu, Yonghuai Al-Obaidi, Ala Jakas, Anthony Li, Longzhuang Aberystwyth University CeredigionSY23 3DB United Kingdom Smart Light Devices Ltd. AberdeenAB24 2YN United Kingdom Texas A and M University Corpus ChristiTX78412 United States

In this paper, we develop a novel method for camera calibration and correction. the novel method first employs a rigidity constraint from the rigid rotation matrix and the radial alignment constraint from the pin-hole camera model to estimate both camera intrinsic and extrinsic parameters with a closed-form solution without considering the camera distortion. then the well-known Levernburg-Marquardt (LM) algorithm is employed to optimize the parameters of interest in two steps: the first step optimizes the first order radial distortion coefficient and the z component of the camera position using a partial image formation model, and the second step optimizes all the parameters of interest using a complete image formation model: 4 intrinsic, 7 extrinsic and 4 distortion parameters. the LM algorithm is initialised either as the parameters estimated so far or as zero. the optimization is achieved through minimising the sum of the squared differences between the distorted projected 3d world control points and their given corresponding distorted image points. the distorted points are finally corrected using again the LM algorithm initialized by the distorted image points themselves, minimizing the squared difference between the distorted corrected point and the given distorted image point. the experimental results based on both synthetic data and real images show that the proposed algorithm produces promising camera calibration and correction results. © 2008 Georgia Institute of Technology.

关键词： Rigidity

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Using Markov Random Fields and algebraic geometry to extract 3d symmetry properties 4

Using Markov Random Fields and algebraic geometry to extract...

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4th international symposium on 3d data processing, visualization and transmission, 3dpvt 2008

作者： Sui, Yunfeng Willis, Andrew R. Dept. of Elec. and Comp. Engineering University of North Carolina at Charlotte CharlotteNC28223 United States

In this paper, we present a new technique for solving the difficult problem of estimating the axis of symmetry for axiallysymmetric surfaces. Accurate solutions to this problem are important in archaeology for systems that seek to reconstruct pottery vessels from measurements of their fragments. Our approach estimates quadratic surfaces at each measured surface point and uses a Markov Random Field superimposed on measured mesh surface to combine surface estimates into surface patches, each of which lies close to a single 3d quadratic surface. For each surface patch, we estimate a quadratic implicit polynomial whose coefficients directly provide an estimate of the unknown axis location and orientation. Using the bootstrap method, distributions for the axis parameters associated with each surface patch are computed. these competing estimates of the global axis are combined using Maximum Likelihood Estimation (MLE) to provide the final estimate. Our approach differs from past approaches by combining estimates derived from large surface regions that include many measurements instead of combining many local (often pointwise) estimates of the surface to determine the global estimate. Estimates from these large regions are more robust to noise and have sufficient data to provide statistical estimates of the uncertainty in the computed estimates. Major benefits of this technique include: (i) a pre-segmentation of the surface to identify noisy, i.e., a-symmetric, regions and (ii) a Bayesian method for merging estimates that makes the axis estimate robust to outliers and highly-variable estimates. © 2008 Georgia Institute of Technology.

关键词： Maximum likelihood estimation

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