Gaussian Mixture Densities for Indexing of Localized Objects in a Video Sequence

The appearance of non-rigid objects in a video stream is highly variable and therefore makes the identification of similar objects very complex. Furthermore, the indexing process of all detected objects is a very challengin- g problem when all appearances of an object would be stored: The database produced would become so large that searching would be intractable. In this paper we present a framework for object-based indexing which on one side increases the robustness of existing feature detectors used for object recognition and on the other side reduces the size of the database. The temporal variation of features of a tracked object in the video-shot is modeled by a mixture of Gaussians. Given a tracked object, this consists in separating the feature distribution into homogeneous clusters. Each cluster corresponds to a stable view of the tracked object. We put in competitions seven different Gaussian models and the number of Gaussian components varies up to four. The EM algorithm is applied to estimate the parameters of the mixture of Gaussians where the number of its components and the Gaussian model are a priori fixed. The choice of the best structure of the data (model and number of Gaussians) is realized by different criteria: BIC, ICL and NEC. The training of the system is done on a set of different tracked objects and the Gaussian mixture classifier is used to recognize new occurrences of objects. Experiments on a video base of twelve different objects are conducted and eight color features are tested. A comparison in the performance of the proposed system and the temporal feature method is analyzed and reported

A Novel Domain Transfer-Based Approach for Unsupervised Thermal Image Super-Resolution

This paper presents a transfer domain strategy to tackle the limitations of low-resolution thermal sensors and generate higher-resolution images of reasonable quality. The proposed technique employs a CycleGAN architecture and uses a ResNet as an encoder in the generator along with an attention module and a novel loss function. The network is trained on a multi-resolution thermal image dataset acquired with three different thermal sensors. Results report better performance benchmarking results on the 2nd CVPR-PBVS-2021 thermal image super-resolution challenge than state-of-the-art methods. The code of this work is available online

Canagliflozin and renal outcomes in type 2 diabetes and nephropathy

BACKGROUND Type 2 diabetes mellitus is the leading cause of kidney failure worldwide, but few effective long-term treatments are available. In cardiovascular trials of inhibitors of sodium–glucose cotransporter 2 (SGLT2), exploratory results have suggested that such drugs may improve renal outcomes in patients with type 2 diabetes. METHODS In this double-blind, randomized trial, we assigned patients with type 2 diabetes and albuminuric chronic kidney disease to receive canagliflozin, an oral SGLT2 inhibitor, at a dose of 100 mg daily or placebo. All the patients had an estimated glomerular filtration rate (GFR) of 30 to <90 ml per minute per 1.73 m2 of body-surface area and albuminuria (ratio of albumin [mg] to creatinine [g], >300 to 5000) and were treated with renin–angiotensin system blockade. The primary outcome was a composite of end-stage kidney disease (dialysis, transplantation, or a sustained estimated GFR of <15 ml per minute per 1.73 m2), a doubling of the serum creatinine level, or death from renal or cardiovascular causes. Prespecified secondary outcomes were tested hierarchically. RESULTS The trial was stopped early after a planned interim analysis on the recommendation of the data and safety monitoring committee. At that time, 4401 patients had undergone randomization, with a median follow-up of 2.62 years. The relative risk of the primary outcome was 30% lower in the canagliflozin group than in the placebo group, with event rates of 43.2 and 61.2 per 1000 patient-years, respectively (hazard ratio, 0.70; 95% confidence interval [CI], 0.59 to 0.82; P=0.00001). The relative risk of the renal-specific composite of end-stage kidney disease, a doubling of the creatinine level, or death from renal causes was lower by 34% (hazard ratio, 0.66; 95% CI, 0.53 to 0.81; P<0.001), and the relative risk of end-stage kidney disease was lower by 32% (hazard ratio, 0.68; 95% CI, 0.54 to 0.86; P=0.002). The canagliflozin group also had a lower risk of cardiovascular death, myocardial infarction, or stroke (hazard ratio, 0.80; 95% CI, 0.67 to 0.95; P=0.01) and hospitalization for heart failure (hazard ratio, 0.61; 95% CI, 0.47 to 0.80; P<0.001). There were no significant differences in rates of amputation or fracture. CONCLUSIONS In patients with type 2 diabetes and kidney disease, the risk of kidney failure and cardiovascular events was lower in the canagliflozin group than in the placebo group at a median follow-up of 2.62 years

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Disorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021. Methods We estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined. Findings Globally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer. Interpretation As the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed. Funding Bill & Melinda Gates Foundation

Construction et Présentation des Vidéos Interactives

The arrival of the MPEG-7 standard for videos requires the creation of high level structures representing their content. The work of this thesis approaches the automatic building of a part of these structures. As a starting point, we use the tools for segmentation of moving objects. Our objectives are then to find similar objects in the video and subsequently use the similarities between camera shots to group shots into video scenes. Once these structures have been built, it is easy to provide video visualization tools for the end users which permit interactive navigation like jumping to the next shot or scene containing a person. The main difficulty lies in the great variability of observed objects: changes in point of view, scales, collusions, etc. The principal contribution of this thesis is the modeling of the variability of observations by a mixture of densities based on the Gaussian mixture theory. This modeling captures various intra-shot appearances of a tracked object and considerably reduces the number of low-level descriptors to be indexed by each tracked object. The proposed formulation led to an implementation designed for different applications: matching of tracked object models represented by Gaussian mixtures, initial building of categories of all objects present in a video by a non-supervised classification technique, extraction of characteristic views and use of detected similar objects for grouping shots into scenes. Keywords: Hyperlinked video, MPEG-7, Object recognition and classification, Variability modeling, Gaussian mixture models, Interactive video navigation, Video structure.L'arrivée de la norme MPEG-7 pour les vidéos exige la création de structures de haut niveau représentant leurs contenus. Le travail de cette thèse aborde l'automatisation de la fabrication d'une partie de ces structures. Comme point de départ, nous utilisons des outils de segmentation des objets en mouvement. Nos objectifs sont alors : retrouver des objets similaires dans la vidéo, utiliser les similarités entre plans caméras pour construire des regroupements de plans en scènes. Une fois ces structures construites, il est facile de fournir aux utilisateurs finaux des outils de visualisation de la vidéo permettant des navigations interactives : par exemple sauter au prochain plan ou scène contenant un personnage. La difficulté principale réside dans la grande variabilité des objets observés : changements de points de vues, d'échelles, occultations, etc. La contribution principale de cette thèse est la modélisation de la variabilité des observations par un mélange de densités basée sur la théorie du mélange gaussien. Cette modélisation permet de capturer les différentes apparences intra-plan de l'objet suivi et de réduire considérablement le nombre des descripteurs de bas niveaux à indexer par objet suivi. Autour de cette contribution se greffent des propositions qui peuvent être vues comme des mises en oeuvre de cette première pour différentes applications : mise en correspondance des objets suivis représentés par des mélanges gaussiens, fabrication initiale des catégories de tous les objets présents dans une vidéo par une technique de classification non supervisée, extraction de vues caractéristiques et utilisation de la détection d'objets similaires pour regrouper des plans en scènes

A spatiotemporal approach for semantic video macro-segmentation

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A Probabilistic Framework of Selecting Effective Key-Frames for Video Browsing and Indexing

To represent effectively the video content, for browsing, indexing and video skimming, the most characteristic frames (called key-frames) should be extracted from given shots. This paper, briefly reviews and evaluates the existing approaches of key-frames extraction; and then introduces a framework of selecting effective key-frames using an unsupervised clustering method. The mixture of Gaussians is used to model the temporal variation of the feature vectors of all frames in the shot. As a result, the feature-based representation of the shot is partitioned into several clusters. From each obtained cluster, firstly the closest frame to the median of its frames is selected as a reference key-frame. Then depending on the variation in time and appearance of the cluster content against the reference key-frame multiple frames can be extracted to represent effectively the cluster. The number of clusters is determined automatically by the Bayes Information Criterion. Experimental results on tracked objects in a real-world video stream are presented which illustrate the performance of the proposed technique