Prospects for b-tagging in ATLAS and tracking commissioning results with cosmic rays

The ability to identify jets containing B hadrons is important for the high-pT physics program of a general-purpose experiment at the LHC such as ATLAS. This capability relies on the very accurate measurements of the parameters of charged tracks provided by the ATLAS Inner Detector. Using millions of cosmic-ray tracks collected during the automn 2008, the ATLAS Inner Detector has been aligned and its tracking performance assessed. Some of the very encouraging results which have been obtained and are relevant for b-tagging are discussed, notably the current level of alignment of the detector and the resolution on the transverse impact parameter of tracks. The various b-tagging algorithms are then described, and their anticipated performance discussed in the light of the cosmic-ray data results. Finaly,the expected accuracy with which the b-tagging performance will be measured in data is mentioned

Spectra of Field Fluctuations in Braneworld Models with Broken Bulk Lorentz Invariance

We investigate five-dimensional braneworld setups with broken Lorentz invariance continuing the developments of our previous paper (arXiv:0712.1136), where a family of static self-tuning braneworld solutions was found. We show that several known braneworld models can be embedded into this family. Then we give a qualitative analysis of spectra of field fluctuations in backgrounds with broken Lorentz invariance. We also elaborate on one particular model and study spectra of scalar and spinor fields in it. It turns out that the spectra we have found possess very peculiar and unexpected properties.Comment: 30 pages, 8 figures, minor corrections, references added, note adde

Signals of Models with Large Extra Dimensions in ATLAS

The generic missing transverse energy signals at LHC for theories having large extra dimensions are discussed. Final states of jets plus missing energy and photons plus missing energy are simulated in the ATLAS detector. The discovery limit of LHC and the methods to determine the parameters of the underlying model are discussed

Dynamic Reconstruction of Complex Planar Objects on Irregular Isothetic Grids

International audienceThe vectorization of discrete regular images has been widely developed in many image processing and synthesis applications, where images are considered as a regular static data. Regardless of final application, we have proposed in [14] a reconstruction algorithm of planar graphical elements on irregular isothetic grids. In this paper, we present a dynamic version of this algorithm to control the reconstruction. Indeed, we handle local refinements to update efficiently our complete shape representation. We also illustrate an application of our contribution for interactive approximation of implicit curves by lines, controlling the topology of the reconstruction

Search for the radion using the ATLAS detector

The possibility of observing the radion using the ATLAS detector at LHC is investigated. Studies on searches for the Standard Model Higgs with the ATLAS detector are re-interpreted to obtain limits on radion decay to gamma-gamma and ZZ(*). The observability of radion decays into Higgs pairs, which subsequently decay into gamma-gamma+b-bbar or tau-tau+b-bbar is then estimate

Unsupervised Polygonal Reconstruction of Noisy Contours by a Discrete Irregular Approach

International audienceIn this paper, we present an original algorithm to build a polygonal reconstruction of noisy digital contours. For this purpose, we first improve an algorithm devoted to the vectorization of discrete irregular isothetic objects. Afterwards we propose to use it to define a reconstruction process of noisy digital contours. More precisely, we use a local noise detector, introduced by Kerautret and Lachaud in IWCIA 2009, that builds a multi-scale representation of the digital contour, which is composed of pixels of various size depending of the local amount of noise. Finally, we compare our approach with previous works, by con- sidering the Hausdorff distance and the error on tangent orientations of the computed line segments to the original perfect contour. Thanks to both synthetic and real noisy objects, we show that our approach has interesting performance, and could be applied in document analysis systems

Understanding Leaves in Natural Images - A Model-Based Approach for Tree Species Identification

International audienceWith the aim of elaborating a mobile application, accessible to anyone and with educational purposes, we present a method for tree species identification that relies on dedicated algorithms and explicit botany-inspired descriptors. Focusing on the analysis of leaves, we developed a working process to help recognize species, starting from a picture of a leaf in a complex natural background. A two-step active contour segmentation algorithm based on a polygonal leaf model processes the image to retrieve the contour of the leaf. Features we use afterwards are high-level geometrical descriptors that make a semantic interpretation possible, and prove to achieve better performance than more generic and statistical shape descriptors alone. We present the results, both in terms of segmentation and classification, considering a database of 50 European broad-leaved tree species, and an implementation of the system is available in the iPhone application Folia

A Model-Based Approach for Compound Leaves Understanding and Identification

International audienceIn this paper, we propose a specific method for the identification of compound-leaved tree species, with the aim of integrating it in an educational smartphone application. Our work is based on dedicated shape models for compound leaves, designed to estimate the number and shape of leaflets. A deformable template approach is used to fit these models and produce a high-level interpretation of the image content. The resulting models are later used for the segmentation of leaves in both plain and natural background images, by the use of multiple region-based active contours. Combined with other botany-inspired descriptors accounting for the morphological properties of the leaves, we propose a classification method that makes a semantic interpretation possible. Results are presented over a set of more than 1000 images from 17 European tree species, and an integration in the existing mobile application Folia is considered

Guiding Active Contours for Tree Leaf Segmentation and Identification

International audienceIn the process of tree identi cation from pictures of leaves in a natural background, retrieving an accurate contour is a challenging and crucial issue. In this paper we introduce a method designed to deal with the obstacles raised by such complex images, for simple and lobed tree leaves. A rst segmentation step based on a light polygonal leaf model is first performed, and later used to guide the evolution of an active contour. Combining global shape descriptors given by the polygonal model with local curvature-based features, the leaves are then classi ed over nearly 50 tree species