Road detection and vehicles tracking by vision for ACC

This article deals with a process designed first to extract the lane of vehicle by on-board monocular vision. This detection process is based upon a recursive updating of a statistical model of the lane obtained by a training phase. Once the lane has been located, a reconstruction algorithm computes the vehicle location on its lane and the 3D shape of the road. Thereafter, we are focus at the detection, location and tracking of front vehicles equipped with specific visual markers in order to achieve an accurate determination of the location and speed of these vehicles. Merging these various informations allows to point out the most dangerous obstacle. Each of these three processes is detailed significant examples are provide.Cet article présente, dans un premier temps, un procédé permettant de détecter la voie de circulation d'un véhicule par vision monoculaire embarquée. Ce processus de détection est basé sur une mise à jour récursive d'un modèle statistique de la voie obtenu par une phase d'apprentissage. Après avoir localisé la voie, un algorithme de reconstruction détermine la position du véhicule dans sa voie de circulation et le profil 3D de la route. Par la suite, nous nous intéressons à la détection, la localisation et surtout le suivi des véhicules situés à l'avant et équipés de marques visuelles afin de déterminer avec précision la position et la vitesse relative de ces véhicules. La combinaison de ces différentes informations permet de déterminer le véhicule le plus dangereux. La description détaillée de chacune des étapes de notre algorithme est suivie d'exemples significatifs

Smart sensing and multisensorial data fusion for road obstacle detection and tracking

In this article, we present a multisensorial solution for road obstacle detection and tracking . This solution is based on a mixe d camera/3D sensor mounted on the front of an experimental vehicle . The multisensor is described . The calibration step enables the matching of the heterogeneous data . Two capabalities of the senso r have been developped : the controlled perception making possible the acquisition of depth data in an area defined in the intensit y image; the visual servoing carrying out the focusing of the laser beam on a moving target detected in the intensity image . These two capabalities allow a Feedback control on the acquisition mode of the sensor according to the environment . ' The perception strategy is based on the selection of the best sensor for a given goal . The obstacle detection is based on th e segmentation and interpretation of depth data which are well suited in this context . However, the rate of acquisition of these dat a is too slow in order to extract the kinematic state of the obstacle . So, the tracking process is based on the collaboration betwee n intensity image processing which ensures the tracking itself and a 3D process which returns the obstacle model size to search in th e image. This algorithm of heterogeneous data fusion, associated with a Kalman filtering, permits to compute the state of obstacles . This work fits into the european project PROMETHEUS . Experimental results have been validated in real situation on the Prola b vehicle .Dans cet article, nous présentons une solution multisensorielle temps réel pour la détection et le suivi d'obstacles sur route. Cette solution est basée sur l'utilisation d'un capteur mixte caméra vidéo/capteur de profondeur placé à l'avant d'un véhicule expérimental. Le capteur multisensoriel est décrit. Le calibrage permet l'alignement des données hétérogènes. Deux facultés du capteur sont développées : la perception dirigée permet l'acquisition d'une image de profondeur dans une zone définie dans l'image de luminance ; l'asservissement visuel réalise la focalisation du faisceau laser sur un point de l'image de luminance. De façon générale, ces facultés permettent un contrôle par rétroaction sur le mode d'acquisition du capteur en fonction de la situation dans laquelle se trouve le système de perception. La stratégie de perception est basée sur la sélection du capteur adéquat pour un objectif donné. La détection d'obstacle repose sur la segmentation et l'interprétation des données de profondeur qui sont d'une grande pertinence dans ce contexte. En revanche, la cadence d'acquisition de ces données n'est pas suffisante si l'on souhaite dériver les caractéristiques cinématiques des obstacles. En conséquence, le suivi des obstacles combine un traitement de l'image de luminance rapide avec un traitement de l'information 3D. Le premier permet de réactualiser la position de l'obstacle afin d'asservir le faisceau laser sur celui-ci et le second assure la connaissance de la taille du modèle de l'obstacle à chercher dans l'image. Cet algorithme de fusion de données hétérogènes accompagné d'un filtrage de Kalman permet d'inférer les caractéristiques cinématiques des obstacles dont la connaissance est indispensable pour aborder ceux-ci dans de bonnes conditions. Ces recherches sont menées dans le cadre du projet européen PROMETHEUS et sont validées en situation réelle à bord du véhicule expérimental Prolab

Transcranial direct current stimulation combined with upper limb functional training in children with spastic, hemiparetic cerebral palsy: study protocol for a randomized controlled trial

The aim of the proposed study is to perform a comparative analysis of functional training effects for the paretic upper limb with and without transcranial direct current stimulation over the primary motor cortex in children with spastic hemiparetic cerebral palsy

Epidemiology of intra-abdominal infection and sepsis in critically ill patients: “AbSeS”, a multinational observational cohort study and ESICM Trials Group Project

Purpose: To describe the epidemiology of intra-abdominal infection in an international cohort of ICU patients according to a new system that classifies cases according to setting of infection acquisition (community-acquired, early onset hospital-acquired, and late-onset hospital-acquired), anatomical disruption (absent or present with localized or diffuse peritonitis), and severity of disease expression (infection, sepsis, and septic shock). Methods: We performed a multicenter (n = 309), observational, epidemiological study including adult ICU patients diagnosed with intra-abdominal infection. Risk factors for mortality were assessed by logistic regression analysis. Results: The cohort included 2621 patients. Setting of infection acquisition was community-acquired in 31.6%, early onset hospital-acquired in 25%, and late-onset hospital-acquired in 43.4% of patients. Overall prevalence of antimicrobial resistance was 26.3% and difficult-to-treat resistant Gram-negative bacteria 4.3%, with great variation according to geographic region. No difference in prevalence of antimicrobial resistance was observed according to setting of infection acquisition. Overall mortality was 29.1%. Independent risk factors for mortality included late-onset hospital-acquired infection, diffuse peritonitis, sepsis, septic shock, older age, malnutrition, liver failure, congestive heart failure, antimicrobial resistance (either methicillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci, extended-spectrum beta-lactamase-producing Gram-negative bacteria, or carbapenem-resistant Gram-negative bacteria) and source control failure evidenced by either the need for surgical revision or persistent inflammation. Conclusion: This multinational, heterogeneous cohort of ICU patients with intra-abdominal infection revealed that setting of infection acquisition, anatomical disruption, and severity of disease expression are disease-specific phenotypic characteristics associated with outcome, irrespective of the type of infection. Antimicrobial resistance is equally common in community-acquired as in hospital-acquired infection

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Location and relative speed estimation of vehicles by monocular vision

International audienc

A Real Time Car Tracker

This paper details a vehicle detection and localization algorithm from a single perspective view. A video camera, embedded in a car, provides a grey scale image of a lead car. This lead vehicle is equipped with three visual marks to make easier low and high level processes. The algorithm is designed for real time implementation. It is conceived from a direct 3D localization method coupled with a tracking method based on a rigidity criteria of the trajectories of N points. The processes are implemented on a specialized hardware architecture to satisfy real time constraints. Keywords : computer vision, real time implementation, car tracking.

TRACKING WITH A PAN-TILT-ZOOM CAMERA FOR AN ACC SYSTEM

In this paper, visual perception of frontal view in intelligent cars is considered. A Pan-Tilt-Zoom (PTZ) camera is used to track preceding vehicles. The aim of this work is to keep the rear view image of the target vehicle stable in scale and position. An efficient real time tracking algorithm is integrated. It is a generic and robust approach, particularly well suited for the detection of scale changes. The camera rotations and zoom are controlled by visual servoing. The methods presented here were tested on real road sequences within the VELAC demonstration vehicle. Experimental results show the effectiveness of such an approach. The perspectives are in the development of a visual sensor combining a PTZ camera and a standard camera. The standard camera has small focal length and is devoted to an analysis of the whole frontal scene. The PTZ camera gives a local view of this scene to increase sensor range and precision. 1

Effects of anodal transcranial direct current stimulation combined with virtual reality for improving gait in children with spastic diparetic cerebral palsy: A pilot, randomized, controlled, double-blind, clinical trial.

To compare the effects of anodal vs. sham transcranial direct current stimulation combined with virtual reality training for improving gait in children with cerebral palsy.A pilot, randomized, controlled, double-blind, clinical trial.Rehabilitation clinics.A total of 20 children with diparesis owing to cerebral palsy.The experimental group received anodal stimulation and the control group received sham stimulation over the primary motor cortex during virtual reality training. All patients underwent the same training programme involving a virtual reality (10 sessions). Evaluations were performed before and after the intervention as well as at the one-month follow-up and involved gait analysis, the Gross Motor Function Measure, the Pediatric Evaluation Disability Inventory and the determination of motor evoked potentials.The experimental group had a better performance regarding gait velocity (experimental group: 0.63 ±0.17 to 0.85 ±0.11???m/s; control group: 0.73 ±0.15 to 0.61 ±0.15???m/s), cadence (experimental group: 97.4 ±14.1 to 116.8 ±8.7???steps/minute; control group: 92.6 ±10.4 to 99.7 ±9.7???steps/minute), gross motor function (dimension D experimental group: 59.7 ±12.8 to 74.9 ±13.8; control group: 58.9 ±10.4 to 69.4 ±9.3; dimension E experimental group: 59.0 ±10.9 to 79.1 ±8.5; control group: 60.3 ±10.1 to 67.4 ±11.4) and independent mobility (experimental group: 34.3 ±5.9 to 43.8 ±75.3; control group: 34.4 ±8.3 to 37.7 ±7.7). Moreover, transcranial direct current stimulation led to a significant increase in motor evoked potential (experimental group: 1.4 ±0.7 to 2.6 ±0.4; control group: 1.3 ±0.6 to 1.6 ±0.4).These preliminary findings support the hypothesis that anodal transcranial direct current stimulation combined with virtual reality training could be a useful tool for improving gait in children with cerebral palsy