A simple and stable feature-preserving smoothing method for contours-based reconstructed meshes
In this paper, we develop a new feature preserving smoothing method for the irregular and coarse meshes reconstructed from 2D contours. To make the feature detecting robust, a new detecting algorithm using the continuity among adjacent contours is proposed. Then the original mesh is subdivided adaptively according to the detected geometric features and smoothed with isotropic method. With the help of that, our algorithm obtains not only the feature-preserving result of anisotropic methods but also the simple and stable process of isotropic ones. After smoothing, the resolution of mesh can be resumed by moving the vertices in the original mesh to the positions of their corresponding vertices in the smoothed adaptive mesh. For smoothing of contours-based reconstructed meshes, experimental results show that our method can smooth the meshes satisfactorily and preserve their geometric features much better than other implemented methods.

title: A mass-spring model for surface mesh deformation based on shape matching
abstract: In this paper, we propose a mass-spring model based on shape matching for real-time deformable modeling in virtual reality systems. By defining a rigid core for surface mesh model and adding a new generalized spring for each mass, our surface mesh model can preserve its original geometric features such as volume and shape. Then, we use shape matching approaches to update the rigid core of the model dynamically so as to simulate global deformations. At last, we adopt an inverse dynamics technique to deal with the resulting deformations. We correct the non-real "super-elastic" effect for linear elastic models so that the visual reality is improved.

title: Dynamic harmonic fields for surface processing
abstract: Harmonic fields have been shown to provide effective guidance for a number of geometry processing problems. In this paper, we propose a method for fast updating of harmonic fields defined on polygonal meshes, enabling real-time insertion and deletion of constraints. Our approach utilizes the penalty method to enforce constraints in harmonic field computation. It maintains the symmetry of the Laplacian system and takes advantage of fast multi-rank updating and downdating of Cholesky factorization, achieving both speed and numerical stability. We demonstrate how the interactivity induced by fast harmonic field update can be utilized in several applications, including harmonic-guided quadrilateral remeshing, vector field design, interactive geometric detail modeling, and handle-driven shape editing and animation transfer with a dynamic handle set.

title: 2D shape deformation based on rigid square matching
abstract: In this paper, we propose a fast and stable method for 2D shape deformation based on rigid square matching. Our method utilizes uniform quadrangular control meshes for 2D shapes and tries to maintain the rigidity of each square in the control mesh during user manipulation. A rigid shape matching method is performed to find an optimal pure rotational transformation for each square in the control mesh. An iterative solver is proposed to compute the final deformation result for the entire control mesh by minimizing the difference between the deformed vertices and their counterparts in the neighboring rigid square. The deformation result on the 2D shape is as rigid as possible and the details of the shape are preserved well. As extensions, we present a shape-aware splitting method to improve the deformation effect for coarse meshes and a simple sketch-based clustering method for skeletal deformation. Experiments with various 2D shapes show that our method is efficient and easy to use, and can provide physically plausible result for shapes of objects in real world. Therefore, our shape deformation method is especially suitable for applications in cartoon character animation.

title: Non-rigid Registration in 3D Implicit Vector Space
abstract: We present an implicit approach for pair-wise non-rigid registration of moving and deforming objects. Shapes of interest are implicitly embedded in the 3D implicit vector space. In this implicit embedding space, registration is performed using a global-to-local framework. Firstly, a non-linear optimization functional defined on the vector distance function is used to find the global alignment between shapes. Secondly, an incremental cubic B-spline free form deformation is used to recover the non-rigid transformation parameters. Local non-rigid registration is posed in terms of minimising an energy functional, for which we give a closed-form linear system and solve it using an improved iterative Gauss-Seidel method. Our approach can consistently produce smooth and continuous registration fields, and correctly establish dense one-to-one correspondences. It can naturally deal with both open partial and closed shapes, and imperfect models with gaps and noise, through its use of the implicit vector representation. Experimental results on several datasets demonstrate the robustness of the proposed method.

title: A Mesh Meaningful Segmentation Algorithm Using Skeleton and Minima-Rule
abstract: In this paper, a hierarchical shape decomposition algorithm is proposed, which integrates the advantages of skeleton-based and minima-rule-based meaningful segmentation algorithms. The method makes use of new geometrical and topological functions of skeleton to define initial cutting critical points, and then employs salient contours with negative minimal principal curvature values to determine natural final boundary curves among parts. And sufficient experiments have been carried out on many meshes, and shown that our framework can provide more reasonable perceptual results than single skeleton-based [8] or minima-rule-based [15] algorithm. In addition, our algorithm not only can divide a mesh of any genus into a collection of genus zero, but also partition level-of-detail meshes into similar parts.

title: Monitoring with behavior view diagrams for debugging
abstract: UML sequence diagrams are widely used during requirements analysis and design for specifying the expected message exchanges among a set of objects in various scenarios for the program to perform a certain task. In this paper, we present the behavior view diagrams, a type of extended sequence diagrams, to facilitate execution monitoring during debugging. Using a behavior view diagram, software developers can precisely specify the runtime objects whose behaviors will be monitored during debugging. Software developers can also specify the important message exchanges to be observed among these objects during the progress of various scenarios, and may further define the monitoring actions to be performed for inspecting the program state when a message exchange is observed. We also present a debugger that can automatically monitor the program execution using the information specified in a behavior view diagram. Through this monitoring, the debugger can not only check whether the scenarios are progressed as intended, but also check whether the actions performed by the program have the the desired effects on the program states. Therefore, it will be useful for detecting and localizing bugs.

title: Gene Specific Co-regulation Discovery: An Improved Approach
abstract: Discovering gene co-regulatory relationships is a new but important research problem in DNA microarray data analysis. The problem of gene specific co-regulation discovery is to, for a particular gene of interest, called the target gene , identify its strongly co-regulated genes and the condition subsets where such strong gene co-regulations are observed. The study on this problem can contribute to a better understanding and characterization of the target gene. The existing method, using the genetic algorithm (GA), is slow due to its expensive fitness evaluation and long individual representation. In this paper, we propose an improved method for finding gene specific co-regulations. Compared with the current method, our method features a notably improved efficiency. We employ k NN Search Table to substantially speed up fitness evaluation in the GA. We also propose a more compact representation scheme for encoding individuals in the GA, which contributes to faster crossover and mutation operations. Experimental results with a real-life gene microarray data set demonstrate the improved efficiency of our technique compared with the current method.

title: Visual Representations

title: Detecting Projected Outliers in High-Dimensional Data Streams
abstract: In this paper, we study the problem of projected outlier detection in high dimensional data streams and propose a new technique, called Stream Projected Ouliter deTector (SPOT), to identify outliers embedded in subspaces. Sparse Subspace Template (SST), a set of subspaces obtained by unsupervised and/or supervised learning processes, is constructed in SPOT to detect projected outliers effectively. Multi-Objective Genetic Algorithm (MOGA) is employed as an effective search method for finding outlying subspaces from training data to construct SST. SST is able to carry out online self-evolution in the detection stage to cope with dynamics of data streams. The experimental results demonstrate the efficiency and effectiveness of SPOT in detecting outliers in high-dimensional data streams.

title: GEOMI: GEOmetry for Maximum Insight
abstract: This paper describes the GEOMI system, a visual analysis tool for the visualisation and analysis of large and complex networks. GEOMI provides a collection of network analysis methods, graph layout algorithms and several graph navigation and interaction methods. GEOMI is part of a new generation of visual analysis tools combining graph visualisation techniques with network analysis methods. GEOMI is available from