Motion retargeting and evaluation for VR-based training of free motions
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-based surface light field morphing
abstract: A surface light field is a function that gives the colors of each object point viewed from different directions. Object representation with a surface light field provides a nice structure for 3D photography. This paper presents a feature-based morphing technique for two objects equipped with surface light fields. The technique consists of geometry morphing and in-between light field mapping. Geometry morphing is accomplished by 3D mesh morphing, where we introduce a vertex merging technique to generate a simpler metamesh. In in-between light field mapping, an in-between object is rendered by extracting necessary fragments from input surface light fields. We also propose an acceleration technique for rendering an in-between object. Experimental results with real and synthetic data show natural and plausible morphing between objects with surface light fields. The proposed morphing technique can be used as an editing tool for 3D photography.

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: Optical Flow Rendering
abstract: This paper proposes a new approach to image-based rendering that generates an image viewed from an arbitrary camera position and orientation by rendering optical flows extracted from reference images. To derive valid optical flows, we develop an analysis technique that improves the quality of stereo matching. Without using any special equipments such as range cameras, this technique constructs reliable optical flows from a sequence of matching results between reference images. We also derive validity conditions of optical flows and show that the obtained flows satisfy those conditions. Since environment geometry is inferred from the optical flows, we are able to generate more accurate images with this additional geometric information. Our approach makes it possible to combine an image rendered from optical flows with an image generated by a conventional rendering technique through a simple Z-buffer algorithm.

title: Local injectivity conditions of 2D and 3D uniform cubic B-spline functions
abstract: Uniform cubic B-spline functions have been used for mapping functions in various areas such as image warping and morphing, 3D deformation, and volume morphing. The injectivity (one-to-one property) of a mapping function is important to obtain good results in these areas. We consider the local injectivity conditions of 2D and 3D uniform cubic B-spline functions. We propose a geometric interpretation of the local injectivity of a uniform cubic B-spline function, with which 2D and 3D cases can be handled in a similar way. Based on the geometric interpretation, we present sufficient conditions for the local injectivity that are represented in terms of control point displacements. These sufficient conditions are simple and easy to check and will be useful to guarantee the injectivity of mapping functions in application areas.

title: Scattered Data Interpolation with Multilevel B-Splines
abstract: The paper describes a fast algorithm for scattered data interpolation and approximation. Multilevel B-splines are introduced to compute a C/sup 2/ continuous surface through a set of irregularly spaced points. The algorithm makes use of a coarse to fine hierarchy of control lattices to generate a sequence of bicubic B-spline functions whose sum approaches the desired interpolation function. Large performance gains are realized by using B-spline refinement to reduce the sum of these functions into one equivalent B-spline function. Experimental results demonstrate that high fidelity reconstruction is possible from a selected set of sparse and irregular samples.

title: Noise-robust automatic speech recognition using mainlobe-resilient time-frequency quantile-based noise estimation
abstract: In standard speech recognition systems in which training data are clean speech, the presence of background noise in received signal can severely deteriorate the recognition performance. This paper presents a simple noise-robust speech recognition system based on a modified noise spectral estimation method called mainlobe-resilient time-frequency quantile-based noise estimation (M-R T-F QBNE), which focuses on the mainlobes at harmonic frequencies. We estimate the global signal-to-noise ratio (SNR) and select a recognition model, which is best matched to the SNR operating range. Experimental results show that the recognition accuracy of the proposed recognition system is higher than that of the AURORA2 clean training baseline by 23%. Compared to multicondition training, the proposed method achieves comparable recognition accuracy.

title: Integer-Magic Spectra Of Amalgamations Of Stars And Cycles
abstract: For any positive integer k; a graph G = (V;E) is said to be ZZ k-magic if there exists a labeling l : E(G) i! ZZ k i f0g such that the induced vertex set labeling l + : V (G) i! ZZ k

title: Increasing the throughput of an adaptive router in network-on-chip (NoC)
abstract: In this paper, we propose a simple and efficient mechanism to increase the throughput of an adaptive router in network-on-chip (NoC). One of the most serious disadvantages of fully adaptive wormhole routers is its performance degradation due to the routing decision time. The key idea to overcome this shortcoming is the use of different clocks in a head flit and body flits, because the body flits can be forwarded immediately and the FIFO usually operates faster than route decision logic in an adaptive router. The major contributions of this paper are: 1) a proposal of a simple and efficient mechanism to improve the performance of fully adaptive wormhole routers, 2) a quantitative evaluation of the proposed mechanism showing that the proposed one can support higher throughput than a conventional one, and 3) an evaluation of hardware overhead for the proposed router. In summary, the proposed clock boosting mechanism enhances the throughput of the original adaptive router by increasing the accepted load and decreasing the average latency in the region of effective bandwidth.

title: Grid services for earthquake science
abstract: We describe an information system architecture for the ACES (Asia–Pacific Cooperation for Earthquake Simulation) community. It addresses several key features of the field—simulations at multiple scales that need to be coupled together; real-time and archival observational data, which needs to be analyzed for patterns and linked to the simulations; a variety of important algorithms including partial differential equation solvers, particle dynamics, signal processing and data analysis; a natural three-dimensional space (plus time) setting for both visualization and observations; the linkage of field to real-time events both as an aid to crisis management and to scientific discovery. We also address the need to support education and research for a field whose computational sophistication is rapidly increasing and spans a broad range. The information system assumes that all significant data is defined by an XML layer which could be virtual, but whose existence ensures that all data is object-based and can be accessed and searched in this form. The various capabilities needed by ACES are defined as grid services, which are conformant with emerging standards and implemented with different levels of fidelity and performance appropriate to the application. Grid Services can be composed in a hierarchical fashion to address complex problems. The real-time needs of the field are addressed by high-performance implementation of data transfer and simulation services. Further, the environment is linked to real-time collaboration to support interactions between scientists in geographically distant locations.

title: Mobility prediction and routing in ad hoc wireless networks
abstract: By exploiting non-random behaviors for the mobility patterns that mobile users exhibit, we can predict the future state of network topology and perform route reconstruction proactively in a timely manner. Moreover, by using the predicted information on the network topology, we can eliminate transmissions of control packets otherwise needed to reconstruct the route and thus reduce overhead. In this paper, we propose various schemes to improve routing protocol performances by using mobility prediction. We then evaluate the effectiveness of using mobility prediction via simulation.