Diurnal Variation of Short-Term Repetitive Maximal Performance and Psychological Variables in Elite Judo Athletes

Objectives: The aim of this study was to examine the effect of time of day on short-term repetitive maximal performance and psychological variables in elite judo athletes.Methods: Fourteen Tunisian elite male judokas (age: 21 ± 1 years, height:172 ± 7 cm, body-mass: 70.0 ± 8.1 kg) performed a repeated shuttle sprint and jump ability (RSSJA) test (6 m × 2 m × 12.5 m every 25-s incorporating one countermovement jump (CMJ) between sprints) in the morning (7:00 a.m.) and afternoon (5:00 p.m.). Psychological variables (Profile of mood states (POMS-f) and Hooper questionnaires) were assessed before and ratings of perceived exertion (RPE) immediately after the RSSJA.Results: Sprint times (p > 0.05) of the six repetition, fatigue index of sprints (p > 0.05) as well as mean (p > 0.05) jump height and fatigue index (p > 0.05) of CMJ did not differ between morning and afternoon. No differences were observed between the two times-of-day for anxiety, anger, confusion, depression, fatigue, interpersonal relationship, sleep, and muscle soreness (p > 0.05). Jump height in CMJ 3 and 4 (p < 0.05) and RPE (p < 0.05) and vigor (p < 0.01) scores were higher in the afternoon compared to the morning. Stress was higher in the morning compared to the afternoon (p < 0.01).Conclusion: In contrast to previous research, repeated sprint running performance and mood states of the tested elite athletes showed no-strong dependency of time-of-day of testing. A possible explanation can be the habituation of the judo athletes to work out early in the morning

Détection et localisation tridimensionnelle par stéréovision d’objets en mouvement dans des environnements complexes : application aux passages à niveau

Within the past years, railways undertakings became interested in the assessment of Level Crossings (LC) safety. We propose in this thesis an Automatic Video-Surveillance system (AVS) at LC for an automatic detection of specific events. The system allows automatically detecting and 3D localizing the presence of one or more obstacles which are motionless at the level crossing. Our research aims at developing an AVS using the passive stereo vision principles. The proposed imaging system uses two cameras to detect and localize any kind of object lying on a railway level crossing. The cameras are placed so that the dangerous zones are well (fully) monitored. The system supervises and estimates automatically the critical situations by detecting objects in the hazardous zone defined as the crossing zone of a railway line by a road or path. The AVS system is used to monitor dynamic scenes where interactions take place among objects of interest (people or vehicles). After a classical image grabbing and digitizing step, the processing is composed of the two following modules: moving and stationary objects detection and 3-D localization. The developed stereo matching algorithm stems from an inference principle based on belief propagation and energy minimization. It takes into account the advantages of local methods for reducing the complexity of the inference step achieved by the belief propagation technique which leads to an improvement in the quality of results. The motion detection module is considered as a constraint which allows improving and speeding up the 3D localization algorithm.La sécurité des personnes et des équipements est un élément capital dans le domaine des transports routiers et ferroviaires. Depuis quelques années, les Passages à Niveau (PN) ont fait l’objet de davantage d'attention afin d'accroître la sécurité des usagers sur cette portion route/rail considérée comme dangereuse. Nous proposons dans cette thèse un système de vision stéréoscopique pour la détection automatique des situations dangereuses. Un tel système permet la détection et la localisation d'obstacles sur ou autour du PN. Le système de vision proposé est composé de deux caméras supervisant la zone de croisement. Nous avons développé des algorithmes permettant à la fois la détection d'objets, tels que des piétons ou des véhicules, et la localisation 3D de ces derniers. L'algorithme de détection d'obstacles se base sur l'Analyse en Composantes Indépendantes et la propagation de croyance spatio-temporelle. L'algorithme de localisation tridimensionnelle exploite les avantages des méthodes locales et globales, et est composé de trois étapes : la première consiste à estimer une carte de disparité à partir d'une fonction de vraisemblance basée sur les méthodes locales. La deuxième étape permet d'identifier les pixels bien mis en correspondance ayant des mesures de confiances élevées. Ce sous-ensemble de pixels est le point de départ de la troisième étape qui consiste à ré-estimer les disparités du reste des pixels par propagation de croyance sélective. Le mouvement est introduit comme une contrainte dans l'algorithme de localisation 3D permettant l'amélioration de la précision de localisation et l'accélération du temps de traitement

Detection and 3D localization of moving and stationary obstacles by stereo vision in complex environments : application at level crossings

La sécurité des personnes et des équipements est un élément capital dans le domaine des transports routiers et ferroviaires. Depuis quelques années, les Passages à Niveau (PN) ont fait l’objet de davantage d'attention afin d'accroître la sécurité des usagers sur cette portion route/rail considérée comme dangereuse. Nous proposons dans cette thèse un système de vision stéréoscopique pour la détection automatique des situations dangereuses. Un tel système permet la détection et la localisation d'obstacles sur ou autour du PN. Le système de vision proposé est composé de deux caméras supervisant la zone de croisement. Nous avons développé des algorithmes permettant à la fois la détection d'objets, tels que des piétons ou des véhicules, et la localisation 3D de ces derniers. L'algorithme de détection d'obstacles se base sur l'Analyse en Composantes Indépendantes et la propagation de croyance spatio-temporelle. L'algorithme de localisation tridimensionnelle exploite les avantages des méthodes locales et globales, et est composé de trois étapes : la première consiste à estimer une carte de disparité à partir d'une fonction de vraisemblance basée sur les méthodes locales. La deuxième étape permet d'identifier les pixels bien mis en correspondance ayant des mesures de confiances élevées. Ce sous-ensemble de pixels est le point de départ de la troisième étape qui consiste à ré-estimer les disparités du reste des pixels par propagation de croyance sélective. Le mouvement est introduit comme une contrainte dans l'algorithme de localisation 3D permettant l'amélioration de la précision de localisation et l'accélération du temps de traitement.Within the past years, railways undertakings became interested in the assessment of Level Crossings (LC) safety. We propose in this thesis an Automatic Video-Surveillance system (AVS) at LC for an automatic detection of specific events. The system allows automatically detecting and 3D localizing the presence of one or more obstacles which are motionless at the level crossing. Our research aims at developing an AVS using the passive stereo vision principles. The proposed imaging system uses two cameras to detect and localize any kind of object lying on a railway level crossing. The cameras are placed so that the dangerous zones are well (fully) monitored. The system supervises and estimates automatically the critical situations by detecting objects in the hazardous zone defined as the crossing zone of a railway line by a road or path. The AVS system is used to monitor dynamic scenes where interactions take place among objects of interest (people or vehicles). After a classical image grabbing and digitizing step, the processing is composed of the two following modules: moving and stationary objects detection and 3-D localization. The developed stereo matching algorithm stems from an inference principle based on belief propagation and energy minimization. It takes into account the advantages of local methods for reducing the complexity of the inference step achieved by the belief propagation technique which leads to an improvement in the quality of results. The motion detection module is considered as a constraint which allows improving and speeding up the 3D localization algorithm

Bayesian curved lane estimation for autonomous driving

International audienceSeveral pieces of research during the last decade in intelligent perception are focused on the development of algorithms allowing vehicles to move efficiently in complex environments. Most of existing approaches suffer from either processing time which do not meet real-time requirements, or inefficient in real complex environment, which also does not meet the full availability constraint of such a critical function. To improve the existing solutions, an algorithm based on curved lane detection by using a Bayesian framework for the estimation of multi-hyperbola parameters is proposed to detect curved lane under challenging conditions. The general idea is to divide a captured image into several parts. The trajectory is modeled by a hyperbola over each part, whose parameters are estimated using the proposed hierarchical Bayesian model. Compared to the existing works in the state of the art, experimental results prove that our approach is more efficient and more precise in road marking detection

Robust lane Extraction using Two-Dimension Declivity

National audienceA new robust lane marking extraction algorithm for monocular vision is proposed based on Two-Dimension Declivity. It is designed for the urban roads with difficult conditions (shadow, high brightness, etc.). In this paper, we propose a locating system which, from an embedded camera, allows lateral positioning of a vehicle by detecting road markings. The primary contribution of the paper is that it supplies a robust method made up of six steps: (i) Image Pre-processing, (ii) Enhanced Declivity Operator (DE), (iii) Mathematical Morphology, (iv) Labeling, (v) Hough Transform and (vi) Line Segment Clustering. The experimental results have shown the high performance of our algorithm in various road scenes. This validation stage has been done with a sequence of simulated images. Results are very promising: more than 90% of marking lines are extracted for less than 12% of false alarm

An Extrinsic Sensor Calibration Framework for Sensor-fusion based Autonomous Vehicle Perception

International audienceIn this paper we deal with sensor alignment problems that appear when implementing sensor fusion-based autonomous vehicle perception. We focus on extrinsic calibration of vision-based and line scan LIDAR sensors. Based on state-of-art solutions, a consistent calibration toolchain is developed, with improvements (accuracy and calibration duration). Additionally, sensor alignment/calibration impact on fusion-based perception is investigated. Experimental results are provided for illustration, using real-world data

6th Conference on Design and Modeling of Mechanical Systems

This book offers a collection of original peer-reviewed contributions presented at the 6th International Congress on Design and Modeling of Mechanical Systems (CMSM’2015), held in Hammamet, Tunisia, from the 23rd to the 25th of March 2015. It reports on both recent research findings and innovative industrial applications in the fields of mechatronics and robotics, dynamics of mechanical systems, fluid structure interaction and vibroacoustics, modeling and analysis of materials and structures, and design and manufacturing of mechanical systems. Since its first edition in 2005, the CMSM Congress has been held every two years with the aim of bringing together specialists from universities and industry to present the state-of-the-art in research and applications, discuss the most recent findings and exchange and develop expertise in the field of design and modeling of mechanical systems. The CMSM Congress is jointly organized by three Tunisian research laboratories: the Mechanical Engineering Laboratory of the National Engineering School of Monastir; the Mechanical Laboratory of Sousse, part of the National Engineering School of Sousse; and the Mechanical, Modeling and Manufacturing Laboratory at the National Engineering School of Sfax

Exploring HLS Optimizations for Efficient Stereo Matching Hardware Implementation

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Using hardware parallelism for reducing power consumption in video streaming applications

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