An evaluation of the pedestrian classification in a multi-domain multi-modality setup

The objective of this article is to study the problem of pedestrian classification across different light spectrum domains (visible and far-infrared (FIR)) and modalities (intensity, depth and motion). In recent years, there has been a number of approaches for classifying and detecting pedestrians in both FIR and visible images, but the methods are difficult to compare, because either the datasets are not publicly available or they do not offer a comparison between the two domains. Our two primary contributions are the following: (1) we propose a public dataset, named RIFIR , containing both FIR and visible images collected in an urban environment from a moving vehicle during daytime; and (2) we compare the state-of-the-art features in a multi-modality setup: intensity, depth and flow, in far-infrared over visible domains. The experiments show that features families, intensity self-similarity (ISS), local binary patterns (LBP), local gradient patterns (LGP) and histogram of oriented gradients (HOG), computed from FIR and visible domains are highly complementary, but their relative performance varies across different modalities. In our experiments, the FIR domain has proven superior to the visible one for the task of pedestrian classification, but the overall best results are obtained by a multi-domain multi-modality multi-feature fusion

Arginine:glycine amidinotransferase (AGAT) deficiency: Clinical features and long term outcomes in 16 patients diagnosed worldwide

Abstract Background Arginine:glycine aminotransferase (AGAT) (GATM) deficiency is an autosomal recessive inborn error of creative synthesis. Objective We performed an international survey among physicians known to treat patients with AGAT deficiency, to assess clinical characteristics and long-term outcomes of this ultra-rare condition. Results 16 patients from 8 families of 8 different ethnic backgrounds were included. 1 patient was asymptomatic when diagnosed at age 3 weeks. 15 patients diagnosed between 16 months and 25 years of life had intellectual disability/developmental delay (IDD). 8 patients also had myopathy/proximal muscle weakness. Common biochemical denominators were low/undetectable guanidinoacetate (GAA) concentrations in urine and plasma, and low/undetectable cerebral creatine levels. 3 families had protein truncation/null mutations. The rest had missense and splice mutations. Treatment with creatine monohydrate (100–800 mg/kg/day) resulted in almost complete restoration of brain creatine levels and significant improvement of myopathy. The 2 patients treated since age 4 and 16 months had normal cognitive and behavioral development at age 10 and 11 years. Late treated patients had limited improvement of cognitive functions. Conclusion AGAT deficiency is a treatable intellectual disability. Early diagnosis may prevent IDD and myopathy. Patients with unexplained IDD with and without myopathy should be assessed for AGAT deficiency by determination of urine/plasma GAA and cerebral creatine levels (via brain MRS), and by GATM gene sequencing

Contributions à la fusion des informations : application à la reconnaissance des obstacles dans les images visible et infrarouge

To continue and improve the detection task which is in progress at INSA laboratory, we focused on the fusion of the information provided by visible and infrared cameras from the view point of an Obstacle Recognition module, this discriminating between vehicles, pedestrians, cyclists and background obstacles. Bimodal systems have been proposed to fuse the information at different levels:of features, SVM's kernels, or SVM’s matching-scores. These were weighted according to the relative importance of the modality sensors to ensure the adaptation (fixed or dynamic) of the system to the environmental conditions. To evaluate the pertinence of the features, different features selection methods were tested by a KNN classifier, which was later replaced by a SVM. An operation of modelsearch, performed by 10 folds cross-validation, provides the optimized kernel for the SVM. The results have proven that all bimodal VIS-IR systems are better than their corresponding monomodal ones.Afin de poursuivre et d'améliorer la tâche de détection qui est en cours à l'INSA, nous nous sommes concentrés sur la fusion des informations visibles et infrarouges du point de vue de reconnaissance des obstacles, ainsi distinguer entre les véhicules, les piétons, les cyclistes et les obstacles de fond. Les systèmes bimodaux ont été proposées pour fusionner l'information à différents niveaux: des caractéristiques, des noyaux SVM, ou de scores SVM. Ils ont été pondérés selon l'importance relative des capteurs modalité pour assurer l'adaptation (fixe ou dynamique) du système aux conditions environnementales. Pour évaluer la pertinence des caractéristiques, différentes méthodes de sélection ont été testés par un PPV, qui fut plus tard remplacée par un SVM. Une opération de recherche de modèle, réalisée par 10 fois validation croisée, fournit le noyau optimisé pour SVM. Les résultats ont prouvé que tous les systèmes bimodaux VIS-IR sont meilleurs que leurs correspondants monomodaux

Contributions to the Information Fusion : application to Obstacle Recognition in Visible and Infrared Images

Afin de poursuivre et d'améliorer la tâche de détection qui est en cours à l'INSA, nous nous sommes concentrés sur la fusion des informations visibles et infrarouges du point de vue de reconnaissance des obstacles, ainsi distinguer entre les véhicules, les piétons, les cyclistes et les obstacles de fond. Les systèmes bimodaux ont été proposées pour fusionner l'information à différents niveaux: des caractéristiques, des noyaux SVM, ou de scores SVM. Ils ont été pondérés selon l'importance relative des capteurs modalité pour assurer l'adaptation (fixe ou dynamique) du système aux conditions environnementales. Pour évaluer la pertinence des caractéristiques, différentes méthodes de sélection ont été testés par un PPV, qui fut plus tard remplacée par un SVM. Une opération de recherche de modèle, réalisée par 10 fois validation croisée, fournit le noyau optimisé pour SVM. Les résultats ont prouvé que tous les systèmes bimodaux VIS-IR sont meilleurs que leurs correspondants monomodaux.To continue and improve the detection task which is in progress at INSA laboratory, we focused on the fusion of the information provided by visible and infrared cameras from the view point of an Obstacle Recognition module, this discriminating between vehicles, pedestrians, cyclists and background obstacles. Bimodal systems have been proposed to fuse the information at different levels:of features, SVM's kernels, or SVM’s matching-scores. These were weighted according to the relative importance of the modality sensors to ensure the adaptation (fixed or dynamic) of the system to the environmental conditions. To evaluate the pertinence of the features, different features selection methods were tested by a KNN classifier, which was later replaced by a SVM. An operation of modelsearch, performed by 10 folds cross-validation, provides the optimized kernel for the SVM. The results have proven that all bimodal VIS-IR systems are better than their corresponding monomodal ones

A Model to Measure the Performance of Human Resources in Organisations

The economic crisis, demography, technology, globalization etc. are all factors which will influence the organizational structures and business strategies. A new business strategy will require, among others, that passive Human Resources Management (HRM) change into an active one with a decisive influence upon business. The vision of an active HRM requires that HR information (IT) dedicated systems assist human resources managers in their decision-making. The existing IT systems predominantly manage the salary calculations and, possibly, the employee's professional development, two of the tasks that a human resources manager has to pursue. However, tasks such as assisting, consulting and engaging the human resources in the organization are equally important. IT systems must also develop into these directions. The present paper proposes a solution to measure the performance of human resources by creating an employee performance indicator (EPI). The paper first describes the economic phenomenon involved in the HR performance process, then the mathematical model is formulated, the algorithm is implemented, the solution of the model is analysed from a technical and economic point of view, and finally the decision is made. We use the weighted arithmetic mean to compute the EPI indicator and the correlation formula to establish the degree of relevance between the EPI indicator and the variables involved in the model. An implementation in R is given

Visible-infrared fusion schemes for road obstacle classification

International audienceIn this article we propose different fusion schemes using information provided by VISible (VIS) and InfraRed (IR) images for road obstacle SVM (Support Vector Machine)-based classification. Three probabilistic approaches for the fusion of VIS and IR images are presented. The early fusion at the feature level yields a bimodal feature vector integrating both VIS and IR data, used to feed an SVM-based classifier. An intermediate fusion at the kernel level combines two different monomodal kernels in order to obtain a particularly flexible Bimodal Kernel (BK), we believe more appropriate for heterogeneous VIS and IR data classification with SVM. The late fusion combines matching scores provided by VIS and IR obstacle recognition modules in order to improve the system performance. An important advantage of these fusion schemes is their capability to adapt to the environmental illumination changes and specific weather conditions due to a modality weighting parameter which allows to adjust the decision of the system according to the relative importance of the VIS and IR modalities. Experiments performed on the TetraVision image database showed that all our fusion-based obstacle classifiers outperform both monomodal VIS and IR obstacle recognizers. The matching score fusion with a dynamic weighting scheme provides the best results compared with both early and intermediate fusion schemes using static modality weights. The BK scheme we propose for VIS–IR fusion would need a greater and better balanced database for learning improvement, since the BK has much more hyper-parameters to be simultaneously optimized than the matching-score fusion

SVM-based Obstacle Classification in Visible and Infrared Images

International audienc