Light field morphing using 2D features
We present a 2D feature-based technique for morphing 3D objects represented by light fields. Existing light field morphing methods require the user to specify corresponding 3D feature elements to guide morph computation. Since slight errors in 3D specification can lead to significant morphing artifacts, we propose a scheme based on 2D feature elements that is less sensitive to imprecise marking of features. First, 2D features are specified by the user in a number of key views in the source and target light fields. Then the two light fields are warped view by view as guided by the corresponding 2D features. Finally, the two warped light fields are blended together to yield the desired light field morph. Two key issues in light field morphing are feature specification and warping of light field rays. For feature specification, we introduce a user interface for delineating 2D features in key views of a light field, which are automatically interpolated to other views. For ray warping, we describe a 2D technique that accounts for visibility changes and present a comparison to the ideal morphing of light fields. Light field morphing based on 2D features makes it simple to incorporate previous image morphing techniques such as nonuniform blending, as well as to morph between an image and a light field.

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: 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-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: 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: Three-Dimensional Volume Reconstruction Based on Trajectory Fusion from Confocal Laser Scanning Microscope Images
abstract: In this paper, we address the problem of 3D volume reconstruction from depth adjacent subvolumes (i.e., sets of image frames) acquired using a confocal laser scanning microscope (CLSM). Our goal is to align sub-volumes by estimating an optimal global image transformation which preserves morphological smoothness of medical structures (called features, e.g., blood vessels) inside of a reconstructed 3D volume. We approached the problem by learning morphological characteristics of structures inside of each sub-volume, i.e. centroid trajectories of features. Next, adjacent sub-volumes are aligned by fusing the morphological characteristics of structures using extrapolation or model fitting. Finally, a global sub-volume to subvolume transformation is computed based on the entire set of fused structures. The trajectory-based 3D volume reconstruction method described here is evaluated with a pair of consecutive physical sections using two evaluation metrics for morphological continu

title: Efficient L1 Regularized Logistic Regression
abstract: L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized logistic regression requires solving a convex optimization problem. However, standard algorithms for solving convex optimization problems do not scale well enough to handle the large datasets encountered in many practical settings. In this paper, we propose an efficient algorithm for L1 regularized logistic regression. Our algorithm iteratively approximates the objective function by a quadratic approximation at the current point, while maintaining the L1 constraint. In each iteration, it uses the efficient LARS (Least Angle Regression) algorithm to solve the resulting L1 constrained quadratic optimization problem. Our theoretical results show that our algorithm is guaranteed to converge to the global optimum. Our experiments show that our algorithm significantly outperforms standard algorithms for solving convex optimization problems. Moreover, our algorithm outperforms four previously published algorithms that were specifically designed to solve the L1 regularized logistic regression problem.

title: Adaptive prefetching technique for shared virtual memory
abstract: Though shared virtual memory (SVM) systems promise low cost solutions for high performance computing, they suffer from long memory latencies. These latencies are usually caused by repetitive invalidation on shared data. Since shared data are accessed through synchronizations and the patterns by which threads synchronize are repetitive, a prefetching scheme based on such repetitiveness would reduce memory latencies. Based on this observation, we propose a prefetching technique which predicts future access behavior by analyzing access history per synchronization variable. Our technique was evaluated on an 8-node SVM system using the SPLASH-2 benchmark. The results show that our technique could achieve 34%-45% reduction in memory access latencies.

title: Backbone construction in selfish wireless networks
abstract: We present a protocol to construct routing backbones in wireless networks composed of selfish participants. Backbones are inherently cooperative, so constructing them in selfish environments is particularly difficult; participants want a backbone to exist (soothers relay their packets) but do not want to join the backbone (so they do not have to relay packets for others).
 We model the wireless backbone as a public good and use impatience as an incentive for cooperation. To determine if and when to donate to this public good, each participant calculates how patient it should be in obtaining the public good. We quantify patience using the Volunteer's Timing Dilemma (VTD), which we extend to general multihop network settings. Using our generalized VTD analysis, each node individually computes as its dominant strategy the amount of time to wait before joining the backbone. We evaluate our protocol using both simulations and an implementation. Our results show that, even though participants in our system deliberately wait before volunteering, a backbone is formed quickly. Further, the quality of the backbone (such as the size and resulting network lifetime) is comparable to that of existing backbone protocols that assume altruistic behavior.

title: Striping delay-sensitive packets over multiple burst-loss channels with random delays
abstract: Multi-homed mobile devices have multiple wireless communication interfaces, each connecting to the Internet via a long range but low speed and bursty WAN link such as a cellular link. We propose a packet striping system for such multi-homed devices - a mapping of delay-sensitive packets by an intermediate gateway to multiple channels, such that the overall performance is enhanced. In particular, we model and analyze the striping of delay-sensitive packets over multiple burst-loss channels with random delays. We first derive the expected packet loss ratio when forward error correction (FEC) is applied for error protection over multiple channels. We next model and analyze the case when the channels are bandwidth-limited with shifted-gamma-distributed transmission delays. We develop a dynamic programming-based algorithm that solves the optimal striping problem for the ARQ, the FEC, and the hybrid FEC/ARQ case.