Connectivity transformation for mesh metamorphosis
In previous mesh morphing techniques, the vertex set and connectivity of an in-between mesh are fixed and only the vertex positions are interpolated between input meshes. With this restriction, to accurately represent both source and target shapes, an in-between mesh should contain a much larger number of vertices than input meshes. This paper proposes a novel approach for mesh morphing, which includes connectivity changes in a metamorphosis. With the approach, an in-between mesh contains only the vertices from the input meshes and so the in-between vertex count does not exceed the sum of source and target vertex counts. The connectivity changes are realized by a sequence of edge swap operation, determined by considering the geometric errors from the input meshes. Experimental results demonstrate that the proposed approach generates almost same in-between shapes as the metamesh-based approach with a much smaller number of vertices.

title: Motion retargeting and evaluation for VR-based training of free motions
abstract: Virtual reality (VR) has emerged as one of the important and effective tools for education and training. Most VR-based training systems are situation based, where the trainees are trained for discrete decision making in special situations presented by the VR environments. In contrast, this paper discusses the application of VR to a different class of training, for learning free motion, often required in sports and the arts. We propose a VR-based motion-training framework that contains an intuitive motion-guiding interface, posture-oriented motion retargeting, and an evaluation and advice scheme for corrective feedback. Applications of the proposed framework to simple fencing training and a dance imitation game are demonstrated .

title: Feature sensitive mesh segmentation with mean shift
abstract: Feature sensitive mesh segmentation is important for many computer graphics and geometric modeling applications. In this paper, we develop a mesh segmentation method, which is capable of producing high-quality shape partitioning. It respects fine shape features and works well on various types of shapes, including natural shapes and mechanical parts. The method combines a procedure for clustering mesh normals with a modification of the mesh clarification technique. For clustering of mesh normals, we adopt Mean Shift, a powerful general purpose technique for clustering scattered data. We demonstrate advantages of our method by comparing it with two state-of-the-art mesh segmentation techniques.

title: Mesh parameterization with a virtual boundary
abstract: Parameterization of a 3D triangular mesh is a fundamental problem in various applications of meshes. The convex combination approach is widely used for parameterization because of its good properties, such as fast computation and one-to-one embedding. However, the approach has a drawback: most boundary triangles have high distortion in the embedding compared with interior ones. In this paper, we present an extension of the convex combination approach that resolves the drawback by using a virtual boundary. Since the virtual boundary is fixed onto a given convex polygon instead of the real boundary, the real boundary triangles can better reflect the shape of the corresponding 3D triangles. The proposedapproach obtains a parameterization of a 3D mesh with less d istortion than with the original convex combination approach.

title: Motif analysis of noisy regular textures
abstract: A regular texture contains a periodic arrangement of a determinable pattern. Motifs of a regular texture are the minimal parallelogrammic sub-regions that can reproduce the texture by tiling. A motif extracted from a regular texture can be used for texture reproduction, texture recognition, and texture compression. However, it is not simple to accurately capture a motif of a regular texture, as the motif may be non-rectangular or arranged in an arbitrary direction. Moreover, when the texture contains additive noises, such as are created by the scanning process, motif analysis becomes more difficult. In this paper, we present an algorithm to obtain a motif of a noisy regular texture in O( mn log mn ) time, where m × n is the size of the texture. The analysis examples demonstrate that the proposed algorithm can robustly derive motifs of noisy regular textures.

title: Out-of-Core Remeshing of Large Polygonal Meshes
abstract: We propose an out-of-core method for creating semi-regular surface representations from large input surface meshes. Our approach is based on a streaming implementation of the MAPS remesher of Lee et al. Our remeshing procedure consists of two stages. First, a simplification process is used to obtain the base domain. During simplification, we maintain the mapping information between the input and the simplified meshes. The second stage of remeshing uses the mapping information to produce samples of the output semi-regular mesh. The out-of-core operation of our method is enabled by the synchronous streaming of a simplified mesh and the mapping information stored at the original vertices. The synchronicity of two streaming buffers is maintained using a specially designed write strategy for each buffer. Experimental results demonstrate the remeshing performance of the proposed method, as well as other applications that use the created mapping between the simplified and the original surface representations

title: Distributed and energy-efficient target localization and tracking in wireless sensor networks
abstract: In this paper, we propose and evaluate a distributed, energy-efficient, light-weight framework for target localization and tracking in wireless sensor networks. Since radio communication is the most energy-consuming operation, this framework aims to reduce the number of messages and the number of message collisions, while providing refined accuracy. The key element of the framework is a novel localization algorithm, called Ratiometric Vector Iteration (RVI). RVI is based on distance ratio estimates rather than absolute distance estimates which are often impossible to calculate. By iteratively updating the estimated location using the distance ratio, RVI localizes the target accurately with only three sensors' participation. After localization, the location of the target is reported to the subscriber. If the target is stationary or moves around within a small area, it is wasteful to report (almost) the same location estimates repeatedly. We, therefore, propose to dynamically adjust a reporting frequency considering the target's movement so that we can reduce the number of report messages while maintaining tracking quality. Extensive simulation results show that the proposed framework combining RVI and the movement-adaptive report scheduling algorithm reduces the localization error and total number of the transmitted messages up to half of those of the existing approaches.

title: An Embedding Framework for Myocardial Velocity Processing with MRI
abstract: This paper presents an embedding framework for myocardial velocity processing with MRI based on a hollow, semi-spherical template. The relationship between vector bundle and manifold mapping is analysed and three different mapping methods that include tangent mapping, normal mapping, and normal-tangent mapping are assessed for their practical value of myocardial contractility analysis. The proposed method provides a basis for consistent volume matching and vector correspondence, in addition to the ease of calculating biomechanical indices such as radial, circumferential and longitudinal strain rates without the concern of boundary effects. Detailed analysis results with both synthetic and in vivo MR velocity data sets are provided.

title: Video Data Indexing by 2D C-Trees
abstract: Video data contains a large amount of spatial and temporal information. The changes of video frames are quite useful for motion analysis and cannot be provided by other media easily. Chang et al. had proposed an effective 2D string approach for spatial indexing of image data. In this paper, we extend this iconic approach and apply it to video data indexing. We propose 2D C-trees to represent the spatial content within individual frames. A video sequence can then be represented and indexed by a temporal set or an ordering set of 2D C-trees. The similarity retrieval of video matching problem becomes the problem of video sequence matching by computing the similarity, or the minimum cost of matched frames. We present three schemes, full-sequence matching, segment matching and subsequence matching, for video information retrieval. The matching schemes can be modified and extended to approximate sequence matching by computing the partial distance for providing a comprehensive retrieval of video data. A prototype video information system is also developed to validate the effectiveness of video data indexing by 2D C-trees.

title: A performance comparison study of ad hoc wireless multicast protocols
abstract: In this paper we investigate the performance of multicast routing protocols in wireless mobile ad hoc networks. An ad hoc network is composed of mobile nodes without the presence of a wired support infrastructure. In this environment, routing/multicasting protocols are faced with the challenge of producing multihop routes under host mobility and bandwidth constraints. In recent years, a number of new multicast protocols of different styles have been proposed for ad hoc networks. However, systematic performance evaluations and comparative analysis of these protocols in a common realistic environment has not yet been performed. In this study, we simulate a set of representative wireless ad hoc multicast protocols and evaluate them in various network scenarios. The relative strengths, weaknesses, and applicability of each multicast protocol to diverse situations are studied and discussed.

title: On stochastic decomposition in the GI/M/1 queue with single exponential vacation
abstract: We consider a GI/M/1 queueing system in which the server takes exactly one exponential vacation each time the system empties. We derive the PGF of the stationary queue length and the LST of the stationary FIFO sojourn time. We show that both the queue length and the sojourn time can be stochastically decomposed into meaningful quantities.