HSIC-based affinity measure for learning on graphs

Pattern Analysis and Applications - The performance of graph-based learning techniques largely relies on the edges defined between the vertices of the graph. These edges that represent the affinity...     

High-performance implementation of in-network traffic pacing for small-buffer networks

Demands on data communication networks continue to drive the need for increasingly faster link speeds. Optical packet switching networks promise to provide data rates that are sufficiently high to satisfy the needs of the future Internet core network. However, a key technological problem with optical packet switching is the very small size of packet buffers that can be implemented in the optical domain. Existing protocols, for example the widely used Transmission Control Protocol (TCP), do not perform well in such small-buffer networks. To address this problem, we have proposed techniques for actively pacing traffic at edge networks to ensure that traffic bursts are reduced or eliminated and thus do not cause packet losses in routers with small buffers. We have also shown that this traffic pacing can improve the performance of conventional networks that use small buffers (e.g., to reduce the cost of buffer memory on routers). A key challenge in this context is to develop systems that can perform such packet pacing efficiently and at high data rates. In this paper, we present the design and prototype of a hardware implementation of our packet pacing technique. We discuss and evaluate design trade-offs and present performance results from an prototype implementation based on a NetFPGA fieldprogrammable gate array system. Our results show that traffic pacing can be implemented with few hardware resources and without reducing system throughput. Therefore, we believe that traffic pacing can be deployed widely to improve the operation of current and future networks.     

Providing Dynamic Visual Information for Collaborative Tasks: Experiments With Automatic Camera Control

One possibility presented by novel communication technologies is the ability for remotely located experts to provide guidance to others who are performing difficult technical tasks in the real world, such as medical procedures or engine repair. In these scenarios, video views and other visual information seem likely to be useful in the ongoing negotiation of shared understanding, or common ground, but actual results with experimental systems have been mixed. One difficulty in designing these systems is achieving a balance between close-up shots that allow for discussion of detail and wide shots that allow for orientation or establishing a mutual point of focus in a larger space. Achieving this balance can be difficult without disorienting or overloading task participants. In this article we present results from two experiments involving three automated camera control systems for remote repair tasks. Results show that a system providing both detailed and overview information was superior to systems providing only one or the other in terms of performance but that some participants preferred the detail-only system.     

Robust pose invariant face recognition using coupled latent space discriminant analysis

We propose a novel pose-invariant face recognition approach which we call Discriminant Multiple Coupled Latent Subspace framework. It finds the sets of projection directions for different poses such that the projected images of the same subject in different poses are maximally correlated in the latent space. Discriminant analysis with artificially simulated pose errors in the latent space makes it robust to small pose errors caused due to a subject’s incorrect pose estimation. We do a comparative analysis of three popular latent space learning approaches: Partial Least Squares (PLSs), Bilinear Model (BLM) and Canonical Correlational Analysis (CCA) in the proposed coupled latent subspace framework. We experimentally demonstrate that using more than two poses simultaneously with CCA results in better performance. We report state-of-the-art results for pose-invariant face recognition on CMU PIE and FERET and comparable results on MultiPIE when using only four fiducial points for alignment and intensity features.     

An efficient method for PET image denoising by combining multi-scale transform and non-local means

Multimedia Tools and Applications - The diagnosis of dementia, particularly in the early stages is very much helpful with Positron emission tomography (PET) image processing. The most important...     

Analytic solution for planar indeterminate impact problems using an energy constraint

This work proposes an analytic method for resolving planar multi-point indeterminate impact problems for rigid-body systems. An event-based approach is used to detect impact events, and constraints consistent with the rigid-body assumption are used to resolve the indeterminacy associated with multi-point impact analysis. The work-energy relation is utilized to determine post-impact velocities based on an energetic coefficient of restitution to model energy dissipation, thereby yielding an energetically consistent set of post-impact velocities based on Stronge’s energetic coefficient of restitution for the treatment of rigid impacts. The effect of stick–slip transition is analyzed based on Coulomb friction. This paper also discusses the transition from impact to contact. This analysis is essential for considering the rocking block problem that is used as an example herein. The predictions of the model for the rocking block problem are compared to experimental results published in the literature. An example of a planar ball undergoing two-point impact is also presented.