Vision-Based Road Detection in Automotive Systems: A Real-Time Expectation-Driven Approach

The main aim of this work is the development of a vision-based road detection system fast enough to cope with the difficult real-time constraints imposed by moving vehicle applications. The hardware platform, a special-purpose massively parallel system, has been chosen to minimize system production and operational costs. This paper presents a novel approach to expectation-driven low-level image segmentation, which can be mapped naturally onto mesh-connected massively parallel SIMD architectures capable of handling hierarchical data structures. The input image is assumed to contain a distorted version of a given template; a multiresolution stretching process is used to reshape the original template in accordance with the acquired image content, minimizing a potential function. The distorted template is the process output.Comment: See http://www.jair.org/ for any accompanying file

Pedestrian detection in far-infrared daytime images using a hierarchical codebook of SURF

One of the main challenges in intelligent vehicles concerns pedestrian detection for driving assistance. Recent experiments have showed that state-of-the-art descriptors provide better performances on the far-infrared (FIR) spectrum than on the visible one, even in daytime conditions, for pedestrian classification. In this paper, we propose a pedestrian detector with on-board FIR camera. Our main contribution is the exploitation of the specific characteristics of FIR images to design a fast, scale-invariant and robust pedestrian detector. Our system consists of three modules, each based on speeded-up robust feature (SURF) matching. The first module allows generating regions-of-interest (ROI), since in FIR images of the pedestrian shapes may vary in large scales, but heads appear usually as light regions. ROI are detected with a high recall rate with the hierarchical codebook of SURF features located in head regions. The second module consists of pedestrian full-body classification by using SVM. This module allows one to enhance the precision with low computational cost. In the third module, we combine the mean shift algorithm with inter-frame scale-invariant SURF feature tracking to enhance the robustness of our system. The experimental evaluation shows that our system outperforms, in the FIR domain, the state-of-the-art Haar-like Adaboost-cascade, histogram of oriented gradients (HOG)/linear SVM (linSVM) and MultiFtrpedestrian detectors, trained on the FIR images

Història dels 25 anys del Comitè de Bioètica de Catalunya

Comité de Bioética de Cataluña; HistoriaBioethics Committee of Catalonia; HistoryComitè de Bioètica de Catalunya; HistòriaEn tota història sempre hi ha algun punt que marqui un abans i un després en el seu inici. En la de la Bioètica a Catalunya aquest punt podria ser el Simposi de l’ abril de 1991 que s’organitzà sota els auspicis del Departament de Sanitat

Nonlinear resonant tunneling in systems coupled to quantum reservoirs

An adiabatic approximation in terms of instantaneous resonances is developed to study the steady-state and time-dependent transport of interacting electrons in biased resonant tunneling heterostructures. The resulting model consists of quantum reservoirs coupled to regions where the system is described by nonlinear ordinary differential equations and has a general conceptual interest.Comment: 4 pages, 3 postscript figure

Adaptative road lanes detection and classification

Proceeding of: 8th International Conference, ACIVS 2006, Antwerp, Belgium, September 18-21, 2006This paper presents a Road Detection and Classification algorithm for Driver Assistance Systems (DAS), which tracks several road lanes and identifies the type of lane boundaries. The algorithm uses an edge filter to extract the longitudinal road markings to which a straight lane model is fitted. Next, the type of right and left lane boundaries (continuous, broken or merge line) is identified using a Fourier analysis. Adjacent lanes are searched when broken or merge lines are detected. Although the knowledge of the line type is essential for a robust DAS, it has been seldom considered in previous works. This knowledge helps to guide the search for other lanes, and it is the basis to identify the type of road (one-way, two-way or freeway), as well as to tell the difference between allowed and forbidden maneuvers, such as crossing a continuous line.Publicad

Energy Deposited in the High Luminosity Inner Triplets of the LHC by Collision Debris

The 14 TeV center of mass proton-proton collisions in the LHC produce not only debris interesting for physics but also showers of particles ending up in the accelerator equipment, in particular in the superconducting magnet coils. Evaluations of this contribution to the heat, that has to be transported by the cryogenic system, have been made to guarantee that the energy deposition in the superconducting magnets does not exceed limits for magnet quenching and the capacity of the cryogenic system. The models of the LHC base-line are detailed and include description of, for energy deposition, essential elements like beam-pipes and corrector magnets. The evaluations made using the Monte-Carlo code FLUKA are compared to previous studies using MARS. For the comparison and consolidation of the calculations, a dedicated study of code comparison for a reduced setup was made