Local feature extraction based facial emotion recognition: a survey

Notwithstanding the recent technological advancement, the identification of facial and emotional expressions is still one of the greatest challenges scientists have ever faced. Generally, the human face is identified as a composition made up of textures arranged in micro-patterns. Currently, there has been a tremendous increase in the use of local binary pattern based texture algorithms which have invariably been identified to being essential in the completion of a variety of tasks and in the extraction of essential attributes from an image. Over the years, lots of LBP variants have been literally reviewed. However, what is left is a thorough and comprehensive analysis of their independent performance. This research work aims at filling this gap by performing a large-scale performance evaluation of 46 recent state-of-the-art LBP variants for facial expression recognition. Extensive experimental results on the well-known challenging and benchmark KDEF, JAFFE, CK and MUG databases taken under different facial expression conditions, indicate that a number of evaluated state-of-the-art LBP-like methods achieve promising results, which are better or competitive than several recent state-of-the-art facial recognition systems. Recognition rates of 100%, 98.57%, 95.92% and 100% have been reached for CK, JAFFE, KDEF and MUG databases, respectively

A Multiple-Objects Recognition Method Based on Region Similarity Measures: Application to Roof Extraction from Orthophotoplans

In this paper, an efficient method for automatic and accurate detection of multiple objects from images using a region similarity measure is presented. This method involves the construction of two knowledge databases: The first one contains several distinctive textures of objects to be extracted. The second one is composed with textures representing background. Both databases are provided by some examples (training set) of images from which one wants to recognize objects. The proposed procedure starts by an initialization step during which the studied image is segmented into homogeneous regions. In order to separate the objects of interest from the image background, an evaluation of the similarity between the regions of the segmented image and those of the constructed knowledge databases is then performed. The proposed approach presents several advantages in terms of applicability, suitability and simplicity. Experimental results obtained from the method applied to extract building roofs from orthophotoplans prove its robustness and performance over popular methods like K Nearest Neighbours (KNN) and Support Vector Machine (SVM)

Segmentation d'images couleur par combinaison LPE-régions/LPE-contours et fusion de régions. Application à la segmentation de toitures à partir d'orthophotoplans

D un point de vue général, les travaux de recherche de cette thèse s inscrivent dans le cadre d une approche globale quiconsiste à extraire des informations relatives aux toitures de bâtiments à partir de photos aériennes (orthophotoplans). L objectifétant de pouvoir reconnaître des toitures extraites d images aériennes en utilisant une base de connaissances, puisaffiner/déformer des modèles 3D générés automatiquement à partir de données géographiques. Pour cela, une premièreétape consiste tout d abord à partitionner l image aérienne en différentes régions d intérêt (pans de toiture, cheminées,chiens assis, fenêtres, etc.), c est la contribution de cette thèse.La méthodologie permettant d atteindre cet objectif est composée de trois étapes : (i) Une étape de simplification qui consisteà simplifier l image initiale avec un couple invariant/gradient approprié et optimisé pour l application. Pour cela, unesérie de tests permettant de choisir, d une part, l invariant colorimétrique le plus approprié parmi 24 invariants et, d autrepart, le meilleur gradient parmi 14 gradients issus de la littérature est réalisée. (ii) La deuxième étape comporte deux stratégiesde segmentation par LPE. L image simplifiée est segmentée d une part par une LPE-régions couplée à une stratégiede fusion de régions, et d autre part, par une LPE-contours. Le processus de fusion de régions intègre des critères defusion fondés sur des grandeurs radiométriques et géométriques adaptés aux particularités des orthophotoplans traités.Une technique de caractérisation 2D des arêtes de toitures par une analyse des segments est proposée afin de calculerl un des critères de fusion. (iii) La troisième étape consiste à combiner les avantages de chaque méthode dans un mêmeschéma de segmentation coopératif afin d aboutir à un résultat de segmentation fiable. Les tests ont été effectués sur unorthophotoplan contenant 100 toitures de complexité variée et évaluées avec le critère de VINET utilisant une segmentationde référence afin de prouver la robustesse et la fiabilité de l approche proposée. Une étape de comparaison permettantde situer les résultats obtenus via notre approche proposée par rapport à ceux obtenus pas les principales méthodes desegmentation de la littérature est finalement effectuée.The work presented in this thesis is developed in a global approach that consists in recognizing roofs extracted from aerialimages using a knowledge database, and bending out 3D models automatically generated from geographical data. Themain step presented in this thesis consists in segmenting roof images in different regions of interest in order to provideseveral measures of roofs (section of roofs, chimneys, roof light, etc).The method aimed at achieving this goal is composed of three principal steps: (i) A simplification step that consists insimplifying the image with an appropriate (optimized for the application) couple of invariant/gradient. For that, several testshave been performed to choose a suitable colorimetric invariant among a set of 24 invariants and define the best gradientamong 14 gradients (eight gray level gradients and six color gradients) of the literature. (ii) The second step is composedof two main treatments: On the one hand, the preliminary orthophotoplan segmentation is produced using the watershedregions applied on the simplified image. An efficient region merging strategy is then applied in order to deal with theover-segmentation problem. The regions merging procedure includes a merging criteria adapted to the orthophotoplanparticularities. In order to calculate one of the merging criteria, a 2D modeling of roof ridges strategy is proposed. Onthe other hand, the simplified image is segmented by the watershed lines. (iii) The third step consists in integrating bothsegmentation strategies by watershed algorithm into a single cooperative segmentation scheme to achieve satisfactorysegmentation results. Tests have been performed on an orthophotoplan containing 100 roofs with varying complexity andevaluated with VINET criteria using a ground truth image segmentation. Comparison results with five popular segmentationtechniques of the literature demonstrates the effectiveness and the reliability of the proposed approach.BELFORT-UTBM-SEVENANS (900942101) / SudocSudocFranceF

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Color image segmentation by combinig watershed-regions / watershed-lines and regions merging : Application to roof segmentation from orthophotoplan

D’un point de vue général, les travaux de recherche de cette thèse s’inscrivent dans le cadre d’une approche globale quiconsiste à extraire des informations relatives aux toitures de bâtiments à partir de photos aériennes (orthophotoplans). L’objectifétant de pouvoir reconnaître des toitures extraites d’images aériennes en utilisant une base de connaissances, puisaffiner/déformer des modèles 3D générés automatiquement à partir de données géographiques. Pour cela, une premièreétape consiste tout d’abord à partitionner l’image aérienne en différentes régions d’intérêt (pans de toiture, cheminées,chiens assis, fenêtres, etc.), c’est la contribution de cette thèse.La méthodologie permettant d’atteindre cet objectif est composée de trois étapes : (i) Une étape de simplification qui consisteà simplifier l’image initiale avec un couple invariant/gradient approprié et optimisé pour l’application. Pour cela, unesérie de tests permettant de choisir, d’une part, l’invariant colorimétrique le plus approprié parmi 24 invariants et, d’autrepart, le meilleur gradient parmi 14 gradients issus de la littérature est réalisée. (ii) La deuxième étape comporte deux stratégiesde segmentation par LPE. L’image simplifiée est segmentée d’une part par une LPE-régions couplée à une stratégiede fusion de régions, et d’autre part, par une LPE-contours. Le processus de fusion de régions intègre des critères defusion fondés sur des grandeurs radiométriques et géométriques adaptés aux particularités des orthophotoplans traités.Une technique de caractérisation 2D des arêtes de toitures par une analyse des segments est proposée afin de calculerl’un des critères de fusion. (iii) La troisième étape consiste à combiner les avantages de chaque méthode dans un mêmeschéma de segmentation coopératif afin d’aboutir à un résultat de segmentation fiable. Les tests ont été effectués sur unorthophotoplan contenant 100 toitures de complexité variée et évaluées avec le critère de VINET utilisant une segmentationde référence afin de prouver la robustesse et la fiabilité de l’approche proposée. Une étape de comparaison permettantde situer les résultats obtenus via notre approche proposée par rapport à ceux obtenus pas les principales méthodes desegmentation de la littérature est finalement effectuée.The work presented in this thesis is developed in a global approach that consists in recognizing roofs extracted from aerialimages using a knowledge database, and bending out 3D models automatically generated from geographical data. Themain step presented in this thesis consists in segmenting roof images in different regions of interest in order to provideseveral measures of roofs (section of roofs, chimneys, roof light, etc).The method aimed at achieving this goal is composed of three principal steps: (i) A simplification step that consists insimplifying the image with an appropriate (optimized for the application) couple of invariant/gradient. For that, several testshave been performed to choose a suitable colorimetric invariant among a set of 24 invariants and define the best gradientamong 14 gradients (eight gray level gradients and six color gradients) of the literature. (ii) The second step is composedof two main treatments: On the one hand, the preliminary orthophotoplan segmentation is produced using the watershedregions applied on the simplified image. An efficient region merging strategy is then applied in order to deal with theover-segmentation problem. The regions merging procedure includes a merging criteria adapted to the orthophotoplanparticularities. In order to calculate one of the merging criteria, a 2D modeling of roof ridges strategy is proposed. Onthe other hand, the simplified image is segmented by the watershed lines. (iii) The third step consists in integrating bothsegmentation strategies by watershed algorithm into a single cooperative segmentation scheme to achieve satisfactorysegmentation results. Tests have been performed on an orthophotoplan containing 100 roofs with varying complexity andevaluated with VINET criteria using a ground truth image segmentation. Comparison results with five popular segmentationtechniques of the literature demonstrates the effectiveness and the reliability of the proposed approach

Segmentation d'images couleur par combinaison LPE-régions/LPE-contours et fusion de régions. Application à la segmentation de toitures à partir d'orthophotoplans

The work presented in this thesis is developed in a global approach that consists in recognizing roofs extracted from aerialimages using a knowledge database, and bending out 3D models automatically generated from geographical data. Themain step presented in this thesis consists in segmenting roof images in different regions of interest in order to provideseveral measures of roofs (section of roofs, chimneys, roof light, etc).The method aimed at achieving this goal is composed of three principal steps: (i) A simplification step that consists insimplifying the image with an appropriate (optimized for the application) couple of invariant/gradient. For that, several testshave been performed to choose a suitable colorimetric invariant among a set of 24 invariants and define the best gradientamong 14 gradients (eight gray level gradients and six color gradients) of the literature. (ii) The second step is composedof two main treatments: On the one hand, the preliminary orthophotoplan segmentation is produced using the watershedregions applied on the simplified image. An efficient region merging strategy is then applied in order to deal with theover-segmentation problem. The regions merging procedure includes a merging criteria adapted to the orthophotoplanparticularities. In order to calculate one of the merging criteria, a 2D modeling of roof ridges strategy is proposed. Onthe other hand, the simplified image is segmented by the watershed lines. (iii) The third step consists in integrating bothsegmentation strategies by watershed algorithm into a single cooperative segmentation scheme to achieve satisfactorysegmentation results. Tests have been performed on an orthophotoplan containing 100 roofs with varying complexity andevaluated with VINET criteria using a ground truth image segmentation. Comparison results with five popular segmentationtechniques of the literature demonstrates the effectiveness and the reliability of the proposed approach.D’un point de vue général, les travaux de recherche de cette thèse s’inscrivent dans le cadre d’une approche globale quiconsiste à extraire des informations relatives aux toitures de bâtiments à partir de photos aériennes (orthophotoplans). L’objectifétant de pouvoir reconnaître des toitures extraites d’images aériennes en utilisant une base de connaissances, puisaffiner/déformer des modèles 3D générés automatiquement à partir de données géographiques. Pour cela, une premièreétape consiste tout d’abord à partitionner l’image aérienne en différentes régions d’intérêt (pans de toiture, cheminées,chiens assis, fenêtres, etc.), c’est la contribution de cette thèse.La méthodologie permettant d’atteindre cet objectif est composée de trois étapes : (i) Une étape de simplification qui consisteà simplifier l’image initiale avec un couple invariant/gradient approprié et optimisé pour l’application. Pour cela, unesérie de tests permettant de choisir, d’une part, l’invariant colorimétrique le plus approprié parmi 24 invariants et, d’autrepart, le meilleur gradient parmi 14 gradients issus de la littérature est réalisée. (ii) La deuxième étape comporte deux stratégiesde segmentation par LPE. L’image simplifiée est segmentée d’une part par une LPE-régions couplée à une stratégiede fusion de régions, et d’autre part, par une LPE-contours. Le processus de fusion de régions intègre des critères defusion fondés sur des grandeurs radiométriques et géométriques adaptés aux particularités des orthophotoplans traités.Une technique de caractérisation 2D des arêtes de toitures par une analyse des segments est proposée afin de calculerl’un des critères de fusion. (iii) La troisième étape consiste à combiner les avantages de chaque méthode dans un mêmeschéma de segmentation coopératif afin d’aboutir à un résultat de segmentation fiable. Les tests ont été effectués sur unorthophotoplan contenant 100 toitures de complexité variée et évaluées avec le critère de VINET utilisant une segmentationde référence afin de prouver la robustesse et la fiabilité de l’approche proposée. Une étape de comparaison permettantde situer les résultats obtenus via notre approche proposée par rapport à ceux obtenus pas les principales méthodes desegmentation de la littérature est finalement effectuée

The investigative approach in the framework of the new programs: study of two cases in France and Morocco

In France as in Morocco, the teaching of science in schools has been subject to various evolutions for many years, and not only to those brought by the new official instructions of each country. For example, the implementation of the “investigation approach” is as much a new approach for the teacher as it is an approach that aims to give more space to the student, which consequently influences the teaching practices. In a case study, we tried to understand what construction of scientific knowledge could be achieved within the framework of an inquiry approach. The analysis of these moments of science led us, in addition to the study of the difficulties of the implementation of an investigative approach and the nature of the knowledge obtained, to question the possible links between the resources mobilized by the teachers and the nature of the knowledge that they make the students construct. This observation converges between several didactic and pedagogical issues and are at the same time for the teacher and the pupil the means of different processes of knowledge construction

Palmprint recognition using state-of-the-art local texture descriptors: a comparative study

International audienceSeveral human being traits can be used as a robust and distinctive identifier for a given person. The palm region of the hand is one of these features that researchers in biometric fields have given a huge consideration in recent years. Many works have been proposed in the literature to design palmprint (an image acquired of the palm region) recognition framework. Extraction of prominent image local features is a critical module in most of these approaches. Local Binary Patterns (LBP) like methods, have emerged as one of the most effective feature extraction techniques. Despite a period of remarkable evolution, neither extensive and comprehensive evaluation nor comparison has been performed to date on a large number of LBP variants and non-LBP texture methods in palmprint recognition problem. Motivated by this, this paper aims to fill that gap and provide a comprehensive comparative study of the performance of a large number of recent texture descriptors in palmprint recognition. Extensive experimental results on the well-known constrained and unconstrained challenging palmprint databases, indicate that a number of tested local texture descriptors, which are evaluated for the first time on palmprint recognition, achieve promising results. Classification results are statistically compared through Wilcoxon signed rank test

Local gradient full-scale transform patterns based off-line text-independent writer identification

International audienceHandwriting based writer identification is one of the reliable components of behavioral biometrics. A huge effort has been done in recent years to improve the writer identification performance. Our paper presents a new and effective off-line text-independent system for writer identification. Extracting features from handwriting substantially impacts the ability of the classification process to identify the query writers. With the use of suitable classifier, a well-designed and discriminative feature extraction improves the classification performance. For that, we introduce a discriminative yet simple feature method, referred to as Local gradient full-Scale Transform Patterns (LSTP). The proposed LSTP algorithm captures salient local writing structure at small regions of interest of the writing. These writing regions are termed as connected components. In the classification stage, we perform Hamming distance based NN classifier to compare and match LSTP feature vectors. The proposed framework is evaluated on 9 well-known handwritten benchmarks. Experimental results show high identification performance against the current state-of-the-art. (C) 2020 Elsevier B.V. All rights reserved