• Korean Journal of Computational Design and Engineering
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• 제12권5호
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• pp.330-343
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• 2007

In this paper, we present a new surface content completion system that can effectively repair both shape and appearance from scanned, incomplete point set inputs. First, geometric holes can be robustly identified from noisy and defective data sets without the need for any normal or orientation information. The geometry and texture information of the holes can then be determined either automatically from the models' context, or manually from users' selection. After identifying the patch that most resembles each hole region, the geometry and texture information can be completed by warping the candidate region and gluing it onto the hole area. The displacement vector field for the exact alignment process is computed by solving a Poisson equation with boundary conditions. Out experiments show that the unified framework, founded upon the techniques of deformable models and PDE modeling, can provide a robust and elegant solution for content completion of defective, complex point surfaces.

• Korean Management Science Review
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• 제23권1호
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• pp.75-85
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• 2006

The rectilinear Steiner tree problem (RSTP) is to find a minimum-length rectilinear interconnection of a set of terminals in the plane. It is well known that the solution to this problem will be the minimal spanning tree(MST) on some set Steiner points. The RSTP is known to be NP-complete. The RSTP has received a lot of attention in the literature and heuristic and optimal algorithms have been proposed. A key performance measure of the algorithm for the RSTP is the reduction rate that is achieved by the difference between the objective value of the RSTP and that of the MST without Steiner points. A hybrid evolutionary strategy on RSTP based upon nodes set is presented. The computational results show that the hybrid evolutionary strategy is better than the previously proposed other heuristic. The average reduction rate of solutions from the evolutionary strategy is about 11.14%, which is almost similar to that of optimal solutions.

• Journal of KIISE:Computing Practices and Letters
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• 제14권5호
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• pp.527-531
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• 2008

For statistical modeling, the model parameters are usually estimated by maximizing a probability measure, such as the likelihood or the posterior. In contrast, a variational Bayesian method treats the parameters of a model as probability distributions and computes optimal distributions for them rather than values. It has been shown that this approach effectively avoids the overfitting problem, which is common with other parameter optimization methods. This paper applies a variational Bayesian technique to surface fitting for height field data. Then, we propose point cloud denoising based on the basic surface fitting technique. Validation experiments and further tests with scan data verify the robustness of the proposed method.

• Journal of Broadcast Engineering
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• 제14권1호
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• pp.81-84
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• 2009

This paper explores the possibility of describing objects from the change in the shape according to the change in viewpoint. Specifically, we sample the shapes from various viewpoints of a 3-D model, and apply dimension reduction by locally linear embedding. A low dimensional distribution of points are constructed, and characteristics of the object are described from this distribution. Also, we propose two 3-D retrieval methods by applying the iterative closest point algorithm, and by applying Fourier transform and measuring similarity by modified Housdorff distance, and present experimental results. The proposed method shows that the change of shape according to the change in viewpoint can describe the characteristics of an object.