Détection d'objets basée sur une approche multicartes

L'organisation perceptive, aujourd'hui couramment utilisée, permet de structurer une image en groupes de primitives significatifs. Notre méthode propose d'utiliser conjointement deux primitives fournissant des informations complémentaires : les segments et les régions. Cette étude a pour objectif de réaliser un système d'organisation perceptive efficace, que nous appliquons sur des images en niveaux de gris représentant des objets polyédriques non texturés. Notre système se décompose en trois parties : La première détecte les primitives et associe les segments aux régions. La deuxième partie génère des hypothèses de groupements de régions associées à une probabilité. Cette probabilité est calculée en utilisant le niveau de gris moyen, la similarité, et la proximité des régions. Enfin, la dernière partie calcule une seconde probabilité d'association, basée sur les lois Gestaltistes (similarité, proximité) associées aux segments de chaque région. La combinaison de ces deux probabilités permet alors de grouper ou non les régions. Notre algorithme effectue des itérations tant que les groupes ne sont pas stabilisés

PHROG: A Multimodal Feature for Place Recognition

International audienceLong-term place recognition in outdoor environments remains a challenge due to high appearance changes in the environment. The problem becomes even more difficult when the matching between two scenes has to be made with information coming from different visual sources, particularly with different spectral ranges. For instance, an infrared camera is helpful for night vision in combination with a visible camera. In this paper, we emphasize our work on testing usual feature point extractors under both constraints: repeatability across spectral ranges and long-term appearance. We develop a new feature extraction method dedicated to improve the repeatability across spectral ranges. We conduct an evaluation of feature robustness on long-term datasets coming from different imaging sources (optics, sensors size and spectral ranges) with a Bag-of-Words approach. The tests we perform demonstrate that our method brings a significant improvement on the image retrieval issue in a visual place recognition context, particularly when there is a need to associate images from various spectral ranges such as infrared and visible: we have evaluated our approach using visible, Near InfraRed (NIR), Short Wavelength InfraRed (SWIR) and Long Wavelength InfraRed (LWIR)

Acoustic resonance detection using statistical methods of voltage envelope characterization in metal halide lamps

Acoustic resonance (AR) phenomenon occurs in metal halide lamps and can cause light flicker, lamp arc bending and rotation, lamp extinction, and in the worst case, arc tube explosion. This study takes place in the context of developing electronic ballasts with robust AR detection and avoidance mechanisms. To this end, a lock-in amplifier is used to measure and characterize lamp voltage root mean square (rms) short-term fluctuations. Statistical criteria based on the standard deviation of this rms value are proposed to assess AR presence and classify its severity. A set of metal halide lamps from different manufacturers and with different powers were tested. The average electrical power and AR level are controlled by adjusting the lamp operating frequency of high-frequency electronic ballast. The proposed criteria enable classifying healthy (without AR) and faulty (with AR) cases based upon either a two-dimensional plane or a boxplot. Regardless of lamp operating power, the results from this study show that the voltage rms variations and the defined criteria are significantly correlated with AR level

A simple high-sensitivity acoustic resonance detection method for metal halide lamps

To detect acoustic resonance (AR) in metal halide (MH) lamps, a simple high-sensitivity method with a multiplier detector is presented in this paper. Voltage envelope variations are measured to evaluate whether AR occurs in MH lamps. The study is focused on improving the sensitivity of an AR detection method. Several manufacturers’ MH lamps are tested in our experiment. In addition, in order to verify the proposed method, the other method of voltage envelope detection is evaluated by a lock-in amplifier with high sensitivity and detection results are analyzed by statistical methods. The results show that the proposed circuit can provide similar sensitivity as the expensive lock-in amplifier to detect AR phenomena and the AR-free and the slight AR level can be easily distinguished

Method to enable LCA analysis through each level of development of a BIM model

Whole Building life cycle assessment (LCA) calculations are increasingly done using building information modeling (BIM) data exports, but some challenges need to be overcome. BIM models lack data for a whole building LCA analysis. To counter this lack of detailed information, manual inputs are often required when using a static BIM model and cannot easily consider recalculations over the duration of the project. This paper presents a method to automatically perform LCA calculations early, at the first level of a BIM model’s development (i.e. the LOD100 level), and to allow for easier updates of the calculation throughout the evolution of the BIM model. To achieve this goal, a novel data layer and format is proposed. This data layer fills the information gap between extracted BIM data and existing LCA data provided by common LCA databases such as ecoinvent

OLED ageing signature characterization under combined thermal and electrical stresses

OLED are appearing at the industrial scale for purposes such as decorative lighting as well as LCD screen back-lighting. One of their main advantages compared to LED is their reduced light intensity: the luminous flux is produced by a much greater surface. Nevertheless there are a number of strong constraints on their allowable operating conditions, which may otherwise dramatically reduce their lifetime. This aspect of OLEDs is up to now not well understood and generally requires the knowledge of the layers and the chemical compounds used to build the device. In this study we submitted commercial OLEDs to limit conditions with respect to their maximum current and temperature. Complete electrical, optical, photometric and thermic characterization was performed on new devices, and repeated at regular intervals during the ageing process. Electrical parameters were measured with a Solartron impedance analyzer and a Keithley Source meter applying current and voltage steps. By the analysis of the indicial response elements of the equivalent linear circuit were extracted. We will illustrate which parameters change the most with the ageing process. The purpose is to predict and quantify the useful lifetime of OLED under electrical and/or thermal stress. Another outcome of importance is related to OLED driver design, namely specifying the end-of-life electrical characteristics. The operating point's significantly drifted from their original values leading sometimes to a doubling of the operating voltage at the same current level

Degradation of the luminance and impedance evolution analysis of an OLED under thermal and electrical stress

Organic light emitting diodes are one of the most innovative light sources. They do not require semiconductor fabrication techniques like the LED family, they are simple to construct and are used in many original applications. The inconvenient of this product is that it does not have a long lasting useful life with more then 10000 hours. Therefore, this paper will present a parametric method to design an aging model of the OLED based on luminance decay and electrical impedance evolution. Accelerated tests using thermal factor and currentdensity will be applied to large warm white OLED panels. A log-normal model for the luminance decay will be merged withdesign of experiments method to include the stress factors as well as impedance characteristics resulting in an effective degradation model that can estimate the lifetime of the OLED

Colossal permittivity and low losses in Ba1–xSrxTiO3–δ reduced nanoceramics

The oxalate route offers a controlled approach to synthesize pure Ba1–xSrxTiO3 (BST) (0 ≤ x ≤ 1) nanoparticles (ϕ ≈ 150 nm in diameter). Reduced BST dense nanoceramics were obtained by spark plasma sintering (SPS) and then annealed for a short time to reach colossal permittivity ( = 105) with low dielectric losses (tan δ = 0.03) at 1 kHz and 300 K. The effects of Ba–Sr substitution on structural, microstructural and electrical properties were analyzed. Comprehensive analysis of the electrical properties indicates that polaron hopping, mediated by Ti3+ ions and oxygen vacancies is the main contributing mechanism to colossal permittivity in Ba-rich BST compounds. Substitution of Ba by Sr reduced the contribution of polaron hopping and led to a decrease of real and imaginary parts of permittivity, while preserving interfacial polarization and yielding better temperature stability. The lowest temperature coefficient of capacitance, or TCC (variation of capacitance between 310 K and 450 K) value, i.e., 44 ppm K−1, is obtained for SrTiO3

InfraPhenoGrid: A scientific workflow infrastructure for Plant Phenomics on the Grid

International audiencePlant phenotyping consists in the observation of physical and biochemical traits of plant genotypes in response to environmental conditions. Challenges , in particular in context of climate change and food security, are numerous. High-throughput platforms have been introduced to observe the dynamic growth of a large number of plants in different environmental conditions. Instead of considering a few genotypes at a time (as it is the case when phenomic traits are measured manually), such platforms make it possible to use completely new kinds of approaches. However, the data sets produced by such widely instrumented platforms are huge, constantly augmenting and produced by increasingly complex experiments, reaching a point where distributed computation is mandatory to extract knowledge from data. In this paper, we introduce InfraPhenoGrid, the infrastructure we designed and deploy to efficiently manage data sets produced by the PhenoArch plant phenomics platform in the context of the French Phenome Project. Our solution consists in deploying scientific workflows on a Grid using a middle-ware to pilot workflow executions. Our approach is user-friendly in the sense that despite the intrinsic complexity of the infrastructure, running scientific workflows and understanding results obtained (using provenance information) is kept as simple as possible for end-users