Robust on-vehicle real-time visual detection of American and European speed limit signs, with a modular Traffic Signs Recognition system

International audienceIn this paper, we present robust visual speed limit signs detection and recognition systems for American and European signs. Both are variants of the same modular traffic signs recognition architecture, with a sign detection step based only on shape-detection (rectangles or circles), which makes our systems insensitive to color variability and quite robust to illumination variations. Instead of a global recognition, our system classifies (or rejects) the speed-limit sign candidates by segmenting potential digits inside them, and then applying a neural network digit recognition. This helps handling global sign variability, as long as digits are properly recognized. The global sign detection rate is around 90% for both (standard) U.S. and E.U. speed limit signs, with a misclassification rate below 1%, and not a single validated false alarm in >150 minutes of recorded videos. The system processes in real-time videos with images of 640x480 pixels, at ~20frames/s on a standard 2.13GHz dual-core laptop

Modular Traffic Sign Recognition applied to on-vehicle real-time visual detection of American and European speed limit signs

International audienceWe present a new modular traffic signs recognition system, successfully applied to both American and European speed limit signs. Our sign detection step is based only on shape-detection (rectangles or circles). This enables it to work on grayscale images, contrary to most European competitors, which eases robustness to illumination conditions (notably night operation). Speed sign candidates are classified (or rejected) by segmenting potential digits inside them (which is rather original and has several advantages), and then applying a neural digit recognition. The global detection rate is ~90% for both (standard) U.S. and E.U. speed signs, with a misclassification rate 150 minutes of video. The system processes in real-time ~20 frames/s on a standard high-end laptop

Improving pan-European speed-limit signs recognition with a new “global number segmentation” before digit recognition

International audienceIn this paper, we present an improved European speed-limit sign recognition system based on an original “global number segmentation” (inside detected circles) before digit segmentation and recognition. The global speed-limit sign detection and correct recognition rate, currently evaluated on videos recorded on a mix of French and German roads, is around 94 %, with a misclassification rate below 1%, and not a single validated false alarm in several hours of recorded videos. Our greyscale-based system is intrinsically insensitive to colour variability and quite robust to illumination variations, as shown by an on-road evaluation under bad weather conditions (cloudy and rainy) which yielded 84% good detection and recognition rate, and by a first night-time on-road evaluation with 75% correct detection rate. Due to recognition occurring at digit level, our system has the potential to be very easily extended to handle properly all variants of speed-limit signs from various European countries. Regarding computation load, videos with images of 640x480 pixels can be processed in real-time at ~20frames/s on a standard 2.13GHz dual-core laptop

Detection and recognition of end-of-speed-limit and supplementary signs for improved european speed limit support

International audienceWe present two new features for our prototype of European Speed Limit Support system: detection and recognition of end-of-speed-limit signs, as well as a framework for detection and recognition of supplementary signs located below main signs and modifying their scope (particular lane, class of vehicle, etc...). The end-of-speed-limit signs are globallyrecognized by a Multi-Layer Perceptron (MLP) neural network. The supplementary signs are detected by applying a rectangle-detection in a region below recognized speed-limit signs, followed by a MLP neural network recognition. A common French+German end-of-speed-limit signs recognition has been designed and successfully tested, yielding 82% detection+recognition. Results for detection and recognition of a first kind of supplementary sign (French exit-lane) are already satisfactory (78% correct detection rate), and our framework can easily be extended to handle other types of supplementary signs. To our knowledge, we are the first team presenting results on detection and recognition of supplementary signs below speed signs, which is a crucial feature for a reliable Speed Limit Support

A CD36 ectodomain mediates insect pheromone detection via a putative tunnelling mechanism.

CD36 transmembrane proteins have diverse roles in lipid uptake, cell adhesion and pathogen sensing. Despite numerous in vitro studies, how they act in native cellular contexts is poorly understood. A Drosophila CD36 homologue, sensory neuron membrane protein 1 (SNMP1), was previously shown to facilitate detection of lipid-derived pheromones by their cognate receptors in olfactory cilia. Here we investigate how SNMP1 functions in vivo. Structure-activity dissection demonstrates that SNMP1's ectodomain is essential, but intracellular and transmembrane domains dispensable, for cilia localization and pheromone-evoked responses. SNMP1 can be substituted by mammalian CD36, whose ectodomain can interact with insect pheromones. Homology modelling, using the mammalian LIMP-2 structure as template, reveals a putative tunnel in the SNMP1 ectodomain that is sufficiently large to accommodate pheromone molecules. Amino-acid substitutions predicted to block this tunnel diminish pheromone sensitivity. We propose a model in which SNMP1 funnels hydrophobic pheromones from the extracellular fluid to integral membrane receptors

Joint interpretation of on-board vision and static GPS cartography for determination of correct speed limit

We present here a first prototype of a "Speed Limit Support" Advance Driving Assistance System (ADAS) producing permanent reliable information on the current speed limit applicable to the vehicle. Such a module can be used either for information of the driver, or could even serve for automatic setting of the maximum speed of a smart Adaptive Cruise Control (ACC). Our system is based on a joint interpretation of cartographic information (for static reference information) with on-board vision, used for traffic sign detection and recognition (including supplementary sub-signs) and visual road lines localization (for detection of lane changes). The visual traffic sign detection part is quite robust (90% global correct detection and recognition for main speed signs, and 80% for exit-lane sub-signs detection). Our approach for joint interpretation with cartography is original, and logic-based rather than probability-based, which allows correct behaviour even in cases, which do happen, when both vision and cartography may provide the same erroneous information

Fusion multi-sources pour l'interprétation d'un environnement routier

Exceeding speed limits is a major cause of road accidents, which could be reduced by the use of robust detection of speed limits that may continuously inform the driver of the proper speed limitation. The work presented in this document relate to the achievement of such a system based on a visual detection of speed limit signs. To make the system robust, it is necessary to merge the results of these detections with information from other sensors to interpret the results of the visual detection. For this aim, two algorithms were developed. First, a specific geographic information system was developed in order to expand the electronic horizon of the vehicle. The fusion process in place addressing these various sources of information is based on model-based rules to overcome the problems inherent to the probabilistic fusion process that can sometimes lead to uncertain situations putting the whole system in global fault. These works are the fruit of collaboration with an automotive supplier and the prototype has been validated experimentally on the road and in real conditions. A ground truth tool has been specially developed to quantify the results. The system shows excellent results with high detection and classification rates for speed limit signs recognition and complex situations analysis.Le dépassement des limitations de vitesse est l'une des causes majeures des accidents de la route, qui pourraient être réduits par l'utilisation de système robuste de détection des limitations de vitesse pouvant continuellement informer le conducteur de la bonne limitation imposée. Les travaux présentés dans ce document portent sur la réalisation d'un tel système basé sur une détection visuelle des panneaux de limitation de vitesse. Afin de rendre le système robuste, il est nécessaire de fusionner les résultats de ces détections avec les informations d'autres capteurs pour interpréter les résultats issus de la détection visuelle. C'est ainsi qu'a été entre autre spécialement développé un capteur cartographique permettant d'avoir une vision plus large sur l'horizon électronique du véhicule, ainsi qu'un système détection des lignes de marquage au sol pour analyser les changements de voie. Le processus de fusion mis en place traitant ces diverses sources d'information est fondé sur des modèles à base de règles permettant de s'affranchir des problèmes inhérents aux processus de fusion probabilistes pouvant parfois mener à des situations de doute mettant le système global en faute. Ces travaux sont le fruit d'une collaboration avec un industriel et le prototype développé a été validé expérimentalement sur route. Un outil de vérité terrain a été spécialement développé pour quantifier les résultats. Le système montre d'excellents résultats en détection et reconnaissance des panneaux de limitation de vitesse ainsi que dans la clarification de situations complexes

Mutations in the palm domain disrupt modulation of acid-sensing ion channel 1a currents by neuropeptides.

Modulation by neuropeptides enhances several functions of acid-sensing ion channels (ASICs), such as pain sensation and acid-induced neuronal injury. The acid-induced opening of ASICs is transient, because of a rapid desensitization. Neuropeptides containing an Arg-Phe-amide motif affect ASIC desensitization and allow continuous activity of ASICs. In spite of the importance of the sustained ASIC activity during prolonged acidification, the molecular mechanisms of ASIC modulation by neuropeptides is only poorly understood. To identify the FRRFa (Phe-Arg-Arg-Phe-amide) binding site on ASIC1a, we carried out an in silico docking analysis and verified functionally the docking predictions. The docking experiments indicated three possible binding pockets, located (1) in the acidic pocket between the thumb, finger, β-ball and palm domains, (2) in a pocket at the bottom of the thumb domain, and (3) in the central vestibule along with the connected side cavities. Functional measurements of mutant ASIC1a confirmed the importance of residues of the lower palm, which encloses the central vestibule and its side cavities, for the FRRFa effects. The combined docking and functional experiments strongly suggest that FRRFa binds to the central vestibule and its side cavities to change ASIC desensitization

Glicocorticóides em afecções do sistema nervoso. Mecanismo de ação

Avaliação dos conhecimentos sobre 0s possíveis mecanismos da atuação glicocorticóide em afecções do sistema nervoso. Os dados sobre os hormônios glicocorticóides, a corticotrofina e o fator liberador da corticotrofina são revistes, bem como aqueles sobre a interação respectiva e o papel desempenhado por estruturas do sistema nervoso. As funções metabólicas dos glicocorticóides são revistas nos aspectos de maior interesse para o tema, após o que é discutida a atuação glicocorticóide em diversos grupos de afecções do sistema nervoso