Direct mesh: a multiresolution approach to terrain visualization
Terrain can be approximated by a triangular mesh consisting millions of 3D points. Multiresolution triangular mesh (MTM) structures are designed to support applications that use terrain data at variable levels of detail (LOD). Typically, an MTM adopts a tree structure where a parent node represents a lower-resolution approximation of its descendants. Given a region of interest (ROI) and a LOD, the process of retrieving the required terrain data from the database is to traverse the MTM tree from the root to reach all the nodes satisfying the ROI and LOD conditions. This process, while being commonly used for multiresolution terrain visualization, is inefficient as either a large number of sequential I/O operations or fetching a large amount of extraneous data is incurred. Various spatial indexes have been proposed in the past to address this problem, however level-by-level tree traversal remains a common practice in order to obtain topological information among the retrieved terrain data. A new MTM data structure called direct mesh is proposed. We demonstrate that with direct mesh the amount of data retrieval can be substantially reduced. Comparing with existing MTM indexing methods, a significant performance improvement has been observed for real-life terrain data.

title: Multiresolution Spatial Databases: Making Web-Based Spatial Applications Faster
abstract: Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

title: A Multiresolution Terrain Model for Efficient Visualization Query Processing
abstract: Multiresolution triangular mesh (MTM) models are widely used to improve the performance of large terrain visualization by replacing the original model with a simplified one. MTM models, which consist of both original and simplified data, are commonly stored in spatial database systems due to their size. The relatively slow access speed of disks makes data retrieval the bottleneck of such terrain visualization systems. Existing spatial access methods proposed to address this problem rely on main-memory MTM models, which leads to significant overhead during query processing. In this paper, we approach the problem from a new perspective and propose a novel MTM called direct mesh that is designed specifically for secondary storage. It supports available indexing methods natively and requires no modification to MTM structure. Experiment results, which are based on two real-world data sets, show an average performance improvement of 5-10 times over the existing methods

title: Workshop Organizers' Message
abstract: International Workshop on Privacy-Preserving Data Analysis (PPDA) 2009 took place at Brisbane, Australia on 21st April, 2009. There were two sessions for this workshop with 2 paper presentations in the first session and 3 presentations in the second session. 
 
With the advancement of information technology and declining hardware price, organizations and companies are able to collect large amount of personal data. Moreover, advanced data analysis and mining techniques have been proposed to derived patterns hidden in data. However, the increasing power in data processing and analysis also raises concerns over the proper usage of personal information. Without proper treatment of the threat of sensitive information leakage, organizations would be reluctant to disclose their data even when there may be great potential gains from the data exploration. Therefore research in the area of privacy preservation is deemed important for both theoretical and practical reasons. PPDA 2009 was held in conjunction with DASFAA 2009 conference, and aims to bring together researchers in different fields related to privacy preserving data analysis and to provide a forum where researchers and practitioners can share and exchange their knowledge and experiences.

title: Biomedical Information Visualization
abstract: The ongoing developments in the fields of molecular biology, genetics, and medical sciences have recently generated an explosion of information collected from living organisms. For the scientist who analyzes these huge amounts of data, information visualization can be a very useful tool.

title: Seeing more than the graph: evaluation of multivariate graph visualization methods
abstract: Many real-world networks are multivariate, i.e., they have attributes associated with nodes and/or edges. Examples include social networks whose nodes represent people and edges represent relationships. There is usually information about each person (such as name, age, and gender) and the relationship (such type, duration, and strength). Besides common graph analysis tasks (such as identifying the most influential or structurally important nodes), there are more complex analyses for multivariate networks. One of these is the multivariate graph clustering, i.e., identifying clusters formed by nodes that have similar attributes and are close to each other in terms of graph distance. For instance, in social network analysis, it is interesting to sociologists whether or not people with similar characteristics (node attributes) are also connected to each other. Currently there are very few visualization methods available for such analysis.
 Graph and multivariate visualization have been well studied separately in the literature. Herman et al. summarized the recent work on graph visualization , and Wong and Bergeron covered the development in multivariate visualization . However, there is relatively less work available on multivariate network visualization. Two types of approaches are commonly used. The first one is the mapping approach, which maps attributes to visual elements of a node or edge. A simple example is to map one attribute to node size and another to node color . A more advanced mapping approach uses glyphs to represent node or edge attributes. One such example is to use the length and width of a rectangle node glyph to represent two node attributes . The second one is the 2.5D approach: it uses the third dimension to present the multivariate information, while the graph is shown on a 2D plane. Examples include the recently proposed "GraphScape" , which adopts a landscape metaphor: each attribute is represented by a two-and-a-half- dimensional surface, whose height indicates its value.
 Each approach has its strength and weakness. The mapping approach is effective of showing numerical value using visual element such as size, but it can be difficult to compare the value of attributes represented by different elements such as size and color. The problem is alleviated by a carefully designed glyph, but visual complexity increases quickly as the number of attributes that a glyph needs to represent grows. The 2.5D approach is good at showing the distribution of attribute values over the network, but the attribute surface could introduce occlusion and affect the visibility of underlying network.
 In this paper, we present a study evaluating the effectiveness of these two approaches for different analysis tasks. We compare the performance of mapping and 2.5D approach in a controlled lab environment. We included both simple tasks (such as identifying nodes with the largest attribute value) and complex tasks (such as multivariate graph clustering). The performance is measured both in terms of accuracy and completion time. The results indicate that statistically mapping approach performs better for the simple tasks, while the 2.5D approach is favored in the complex task. The outcomes from this study provide some guidelines for the design of effective multivariate graph visualization for different analysis tasks.

title: A Pilot Study of Robot-Assisted Cochlear Implant Surgery Using Steerable Electrode Arrays
abstract: This paper presents results of a pilot study evaluating the efficacy of robotic assistance using novel steerable electrode arrays for cochlear implant surgery. The current surgical setup of cochlear implant surgery is briefly reviewed and its limitations are highlighted. In an effort to reduce trauma to the structure of the cochlea, the kinematics and path planning for novel cochlear steerable electrodes are developed to minimize the interaction forces between the electrode and the cochlea. An experimental robotic system is used to compare the electrode insertion forces of steerable implants with those of nonsteerable electrodes. The results of these experiments show about 70% reduction in the insertion forces when steerable electrodes are used with our proposed path planning and control. A distance metric explaining this reduction in the insertion force is defined and experimentally validated. Although this is only a preliminary study, we believe that these results provide a strong indication to the potential of robot-assisted cochlear implant surgery to provide a significant reduction in trauma rates during cochlear implant surgery.

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: A simple and stable feature-preserving smoothing method for contours-based reconstructed meshes
abstract: 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: Intrinsic Wrench Estimation and Its Performance Index for Multisegment Continuum Robots
abstract: This paper presents the intrinsic capability of full-wrench estimation of multisegment continuum robots with multiple flexible backbones. Intrinsic-full-wrench estimation refers to the ability of continuum robots to also serve as force and moment sensors by using measurements of axial loads on their backbones. This end-effector-as-sensor approach fulfills the rapidly increasing needs for miniature-robotic-surgical tools with haptic sensing ability subject to various limitations, such as size, magnetic resonance imaging (MRI) compatibility, sterilizability, etc. A performance index for the intrinsic wrench-sensing capability is introduced and evaluated to show how this index can serve as a design guide for continuum robots that provide force sensing.

title: Partial intrinsic reflectional symmetry of 3D shapes
abstract: While many 3D objects exhibit various forms of global symmetries, prominent intrinsic symmetries which exist only on parts of an object are also well recognized. Such partial symmetries are often seen as more natural than a global one, even when the symmetric parts are under complex pose. We introduce an algorithm to extract partial intrinsic reflectional symmetries (PIRS) of a 3D shape. Given a closed 2-manifold mesh, we develop a voting scheme to obtain an intrinsic reflectional symmetry axis (IRSA) transform, which is a scalar field over the mesh that accentuates prominent IRSAs of the shape. We then extract a set of explicit IRSA curves on the shape based on a refined measure of local reflectional symmetry support along a curve. The iterative refinement procedure combines IRSA-induced region growing and region-constrained symmetry support refinement to improve accuracy and address potential issues arising from rotational symmetries in the shape. We show how the extracted IRSA curves can be incorporated into a conventional mesh segmentation scheme so that the implied symmetry cues can be utilized to obtain more meaningful results. We also demonstrate the use of IRSA curves for symmetry-driven part repair.