Multi-scale line drawings from 3D meshes
We present a method to view-dependently control the size of shape features depicted in computer-generated line drawings of 3D meshes. Our method exhibits good temporal coherence during level of detail transitions, and is fast because the calculations are carried out entirely on the GPU. The strategy is to pre-compute, via a digital geometry processing technique, a sequence of filtered versions of the mesh that eliminate shape features at progressively larger scales. Each filtered mesh retains the original connectivity, providing a direct correspondence between meshes.At run-time, the meshes are loaded onto the graphics card and a vertex program interpolates curvatures and positions between corresponding vertices in adjacent meshes of the sequence. A fragment program then renders silhouettes and suggestive contours to produce a line drawing for which the size of depicted shape features follows a user-specified "target size". For example, we can depict fine shape features over nearby surfaces, and appropriately coarse-scaled features in more distant regions. More general level-of-detail policies could be implemented on top of our approach by letting the target size vary with scene attributes such as depth, image location, or annotations provided by the scene designer.

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: 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: 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: 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: 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: 3D Medical Volume Reconstruction Using Web Services
abstract: We address the problem of 3D medical volume reconstruction using Web services. The use of proposed Web services is motivated by the fact that the problem of 3D medical volume reconstruction requires significant computer resources and human expertise in medical and computer science areas. Web services were implemented as an additional layer to a dataflow framework called data to knowledge. In the collaboration between UIC and NCSA, pre-processed input images at NCSA were made accessible to medical collaborators for registration. Every time medical collaborators inspected images and selected corresponding features for registration, the Web server at NCSA was contacted and the registration processing query was executed using the image to knowledge library of registration methods. Co-registered frames were returned for verification by medical collaborators in a new window. This paper presents 3D volume reconstruction problem requirements, architecture of the developed prototype system and the tradeoffs of our system design.

title: Scale-Space Derived From B-Splines
abstract: This paper proposes a scale-space theory based on B-spline kernels. Our aim is twofold: 1) present a general framework, and show how B-splines provide a flexible tool to design various scale-space representations. In particular, we focus on the design of continuous scale-space and dyadic scale-space frame representations. A general algorithm is presented for fast implementation of continuous scale-space at rational scales. In the dyadic case, efficient frame algorithms are derived using B-spline techniques to analyze the geometry of an image. The relationship between several scale-space approaches is explored. The behavior of edge models, the properties of completeness, causality, and other properties in such a scale-space representation are examined in the framework of B-splines. It is shown that, besides the good properties inherited from the Gaussian kernel, the B-spline derived scale-space exhibits many advantages for modeling visual mechanism including the efficiency, compactness, orientation feature and parallel structure.

title: An efficient lock protocol for home-based lazy release consistency
abstract: Home-based lazy release consistency (HLRC) shows poor performance on lock based applications because of two reasons: a whole page is fetched on a page fault while actual modification is much smaller; and a home is at the fixed location while the access pattern is migratory. We present an efficient lock protocol for HLRC. In this protocol, the pages that are expected to be used by the acquirer are selectively updated using diffs. The diff accumulation problem is minimized by limiting the size of diffs to be sent for each page. Our protocol reduces the number of page faults inside critical sections because pages can be updated by applying locally stored diffs. This reduction yields the reduction of average lock waiting time and the reduction of message amount. The experiment with five applications shows that our protocol archives 2%-40% speedup against base HLRC for four applications.

title: Training Algorithm with Incomplete Data for Feed-Forward Neural Networks
abstract: A new algorithm is developed to train feed-forward neural networks for non-linear input-to-output mappings with small incomplete data in arbitrary distributions. The developed Training-EStimation-Training (TEST) algorithm consists of 3 steps, i.e., (1) training with the complete portion of the training data set, (2) estimation of the missing attributes with the trained neural networks, and (3) re-training the neural networks with the whole data set. Error back propagation is still applicable to estimate the missing attributes. Unlike other training methods with missing data, it does not assume data distribution models which may not be appropriate for small training data. The developed TEST algorithm is first tested for the Iris benchmark data. By randomly removing some attributes from the complete data set and estimating the values latter, accuracy of the TEST algorithm is demonstrated. Then it is applied to the Diabetes benchmark data, of which about 50% contains missing attributes. Compared with other existing algorithms, the proposed TEST algorithm results in much better recognition accuracy for test data.

title: An effective hardware architecture for bump mapping using angular operation
abstract: In this paper, we propose an effective bump mapping algorithm that utilizes the reference space with the polar coordinate system and also propose a new hardware architecture associated with the proposed bump mapping algorithm. The proposed architecture reduces the computations to transform the vectors from the object space into the reference space by using a new vector rotation method. It also reduces the computations for the illumination calculation by using the law of cosine. Compared with the previous approaches, the proposed architecture reduces multiplication operations up to 78%.