News from FormCalc and LoopTools

The FormCalc package automates the computation of FeynArts amplitudes up to one loop including the generation of a Fortran code for the numerical evaluation of the squared matrix element. Major new or enhanced features in Version 5 are: iterative build-up of essentially arbitrary phase-spaces including cuts, convolution with density functions, and uniform treatment of kinematical variables. The LoopTools library supplies the one-loop integrals necessary for evaluating the squared matrix element. Its most significant extensions in Version 2.2 are the five-point family of integrals, and complex and alternate versions.Comment: 5 pages, to appear in the proceedings of the 7th International Symposium on Radiative Corrections (RADCOR05), Shonan Village, Japan, 200

Large Margin Object Tracking with Circulant Feature Maps

Structured output support vector machine (SVM) based tracking algorithms have shown favorable performance recently. Nonetheless, the time-consuming candidate sampling and complex optimization limit their real-time applications. In this paper, we propose a novel large margin object tracking method which absorbs the strong discriminative ability from structured output SVM and speeds up by the correlation filter algorithm significantly. Secondly, a multimodal target detection technique is proposed to improve the target localization precision and prevent model drift introduced by similar objects or background noise. Thirdly, we exploit the feedback from high-confidence tracking results to avoid the model corruption problem. We implement two versions of the proposed tracker with the representations from both conventional hand-crafted and deep convolution neural networks (CNNs) based features to validate the strong compatibility of the algorithm. The experimental results demonstrate that the proposed tracker performs superiorly against several state-of-the-art algorithms on the challenging benchmark sequences while runs at speed in excess of 80 frames per second. The source code and experimental results will be made publicly available

Solution of linear ill-posed problems using overcomplete dictionaries

In the present paper we consider application of overcomplete dictionaries to solution of general ill-posed linear inverse problems. Construction of an adaptive optimal solution for such problems usually relies either on a singular value decomposition or representation of the solution via an orthonormal basis. The shortcoming of both approaches lies in the fact that, in many situations, neither the eigenbasis of the linear operator nor a standard orthonormal basis constitutes an appropriate collection of functions for sparse representation of the unknown function. In the context of regression problems, there have been an enormous amount of effort to recover an unknown function using an overcomplete dictionary. One of the most popular methods, Lasso, is based on minimizing the empirical likelihood and requires stringent assumptions on the dictionary, the, so called, compatibility conditions. While these conditions may be satisfied for the original dictionary functions, they usually do not hold for their images due to contraction imposed by the linear operator. In what follows, we bypass this difficulty by a novel approach which is based on inverting each of the dictionary functions and matching the resulting expansion to the true function, thus, avoiding unrealistic assumptions on the dictionary and using Lasso in a predictive setting. We examine both the white noise and the observational model formulations and also discuss how exact inverse images of the dictionary functions can be replaced by their approximate counterparts. Furthermore, we show how the suggested methodology can be extended to the problem of estimation of a mixing density in a continuous mixture. For all the situations listed above, we provide the oracle inequalities for the risk in a finite sample setting. Simulation studies confirm good computational properties of the Lasso-based technique

IVOA Recommendation: VOTable Format Definition Version 1.3

This document describes the structures making up the VOTable standard. The main part of this document describes the adopted part of the VOTable standard; it is followed by appendices presenting extensions which have been proposed and/or discussed, but which are not part of the standard

Evaluating rules of interaction for object manipulation in cluttered virtual environments

A set of rules is presented for the design of interfaces that allow virtual objects to be manipulated in 3D virtual environments (VEs). The rules differ from other interaction techniques because they focus on the problems of manipulating objects in cluttered spaces rather than open spaces. Two experiments are described that were used to evaluate the effect of different interaction rules on participants' performance when they performed a task known as "the piano mover's problem." This task involved participants in moving a virtual human through parts of a virtual building while simultaneously manipulating a large virtual object that was held in the virtual human's hands, resembling the simulation of manual materials handling in a VE for ergonomic design. Throughout, participants viewed the VE on a large monitor, using an "over-the-shoulder" perspective. In the most cluttered VEs, the time that participants took to complete the task varied by up to 76% with different combinations of rules, thus indicating the need for flexible forms of interaction in such environments