Video event detection and visual data pro cessing for multimedia applications

Cette thèse (i) décrit une procédure automatique pour estimer la condition d'arrêt des méthodes de déconvolution itératives basées sur un critère d'orthogonalité du signal estimé et de son gradient à une itération donnée; (ii) présente une méthode qui décompose l'image en une partie géométrique (ou "cartoon") et une partie "texture" en utilisation une estimation de paramètre et une condition d'arrêt basées sur la diffusion anisotropique avec orthogonalité, en utilisant le fait que ces deux composantes. "cartoon" et "texture", doivent être indépendantes; (iii) décrit une méthode pour extraire d'une séquence vidéo obtenue à partir de caméra portable les objets de premier plan en mouvement. Cette méthode augmente la compensation de mouvement de la caméra par une nouvelle estimation basée noyau de la fonction de probabilité de densité des pixels d'arrière-plan. Les méthodes présentées ont été testées et comparées aux algorithmes de l'état de l'art.This dissertation (i) describes an automatic procedure for estimating the stopping condition of non-regularized iterative deconvolution methods based on an orthogonality criterion of the estimated signal and its gradient at a given iteration; (ii) presents a decomposition method that splits the image into geometric (or cartoon) and texture parts using anisotropic diffusion with orthogonality based parameter estimation and stopping condition, utilizing the theory that the cartoon and the texture components of an image should be independent of each other; (iii) describes a method for moving foreground object extraction in sequences taken by wearable camera, with strong motion, where the camera motion compensated frame differencing is enhanced with a novel kernel-based estimation of the probability density function of the background pixels. The presented methods have been thoroughly tested and compared to other similar algorithms from the state-of-the-art.BORDEAUX1-Bib.electronique (335229901) / SudocSudocFranceF

Wearable video monitoring of people with age Dementia : Video indexing at the service of helthcare

International audienceExploration of video surveillance material for healthcare becomes a reality in medical research. In this paper we propose a video monitoring system with wearable cameras for early diagnostics of Dementia. A video acquisition set-up is designed and the methods are developed for indexing the recorded video. The noisiness of audio-visual material and its particularity yield challenging problems for automatic indexing of this content

Twenty-three unsolved problems in hydrology (UPH) – a community perspective

This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through on-line media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focussed on process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come

Video event detection and visual data pro cessing for multimedia applications

Cette thèse (i) décrit une procédure automatique pour estimer la condition d'arrêt des méthodes de déconvolution itératives basées sur un critère d'orthogonalité du signal estimé et de son gradient à une itération donnée; (ii) présente une méthode qui décompose l'image en une partie géométrique (ou "cartoon") et une partie "texture" en utilisation une estimation de paramètre et une condition d'arrêt basées sur la diffusion anisotropique avec orthogonalité, en utilisant le fait que ces deux composantes. "cartoon" et "texture", doivent être indépendantes; (iii) décrit une méthode pour extraire d'une séquence vidéo obtenue à partir de caméra portable les objets de premier plan en mouvement. Cette méthode augmente la compensation de mouvement de la caméra par une nouvelle estimation basée noyau de la fonction de probabilité de densité des pixels d'arrière-plan. Les méthodes présentées ont été testées et comparées aux algorithmes de l'état de l'art.This dissertation (i) describes an automatic procedure for estimating the stopping condition of non-regularized iterative deconvolution methods based on an orthogonality criterion of the estimated signal and its gradient at a given iteration; (ii) presents a decomposition method that splits the image into geometric (or cartoon) and texture parts using anisotropic diffusion with orthogonality based parameter estimation and stopping condition, utilizing the theory that the cartoon and the texture components of an image should be independent of each other; (iii) describes a method for moving foreground object extraction in sequences taken by wearable camera, with strong motion, where the camera motion compensated frame differencing is enhanced with a novel kernel-based estimation of the probability density function of the background pixels. The presented methods have been thoroughly tested and compared to other similar algorithms from the state-of-the-art

Video event detection and visual data pro cessing for multimedia applications

Cette thèse (i) décrit une procédure automatique pour estimer la condition d'arrêt des méthodes de déconvolution itératives basées sur un critère d'orthogonalité du signal estimé et de son gradient à une itération donnée; (ii) présente une méthode qui décompose l'image en une partie géométrique (ou "cartoon") et une partie "texture" en utilisation une estimation de paramètre et une condition d'arrêt basées sur la diffusion anisotropique avec orthogonalité, en utilisant le fait que ces deux composantes. "cartoon" et "texture", doivent être indépendantes; (iii) décrit une méthode pour extraire d'une séquence vidéo obtenue à partir de caméra portable les objets de premier plan en mouvement. Cette méthode augmente la compensation de mouvement de la caméra par une nouvelle estimation basée noyau de la fonction de probabilité de densité des pixels d'arrière-plan. Les méthodes présentées ont été testées et comparées aux algorithmes de l'état de l'art.This dissertation (i) describes an automatic procedure for estimating the stopping condition of non-regularized iterative deconvolution methods based on an orthogonality criterion of the estimated signal and its gradient at a given iteration; (ii) presents a decomposition method that splits the image into geometric (or cartoon) and texture parts using anisotropic diffusion with orthogonality based parameter estimation and stopping condition, utilizing the theory that the cartoon and the texture components of an image should be independent of each other; (iii) describes a method for moving foreground object extraction in sequences taken by wearable camera, with strong motion, where the camera motion compensated frame differencing is enhanced with a novel kernel-based estimation of the probability density function of the background pixels. The presented methods have been thoroughly tested and compared to other similar algorithms from the state-of-the-art

Detection of moving foreground objects in videos with strong camera motion

International audienceIn this paper, we propose a novel method for moving foreground object extraction in sequences taken by a wearable camera, with strong motion. We use camera motion compensated frame differencing, enhanced with a novel kernel-based estimation of the probability density function of background pixels. The probability density functions are used for filtering false foreground pixels on the motion compensated difference frame. The estimation is based on a limited number of measurements; therefore, we introduce a special, spatio-temporal sample point selection and an adaptive thresholding method to deal with this challenge. Foreground objects are built with the DBSCAN algorithm from detected foreground pixels

A compilation of data on European flash floods

Flash floods are one of the most significant natural hazards in Europe, causing serious risk to life and destruction of buildings and infrastructure. This type of flood, often affecting ungauged watersheds, remains nevertheless a poorly documented phenomenon. To address the gap in available information, and particularly to assess the possible ranges for peak discharges on watersheds with area smaller than 500 km2 and to describe the geography of the hazard across Europe, an intensive data compilation has been carried out for seven European hydrometeorological regions. This inventory is the first step towards an atlas of extreme flash floods in Europe. It contains over 550 documented events. This paper aims at presenting the data compilation strategy, the content of the elaborated data base and some preliminary data analysis results. The initial observations show that the most extreme flash floods are greater in magnitude in the Mediterranean countries than in the inner continental countries and that there is a strong seasonality to flash flood occurrence revealing different climatic forcing mechanisms in each region

TAZ Expression as a Prognostic Indicator in Colorectal Cancer

Agency of Science, Technology, and Research (A*STAR), SingaporeThe Hippo pathway restricts the activity of transcriptional coactivators TAZ (WWTR1) and YAP. TAZ and YAP are reported to be overexpressed in various cancers, however, their prognostic significance in colorectal cancers remains unstudied. The expression levels of TAZ and YAP, and their downstream transcriptional targets, AXL and CTGF, were extracted from two independent colon cancer patient datasets available in the Gene Expression Omnibus database, totaling 522 patients. We found that mRNA expressions of both TAZ and YAP were positively correlated with those of AXL and CTGF (p<0.05). High level mRNA expression of TAZ, AXL or CTGF significantly correlated with shorter survival. Importantly, patients co-overexpressing all 3 genes had a significantly shorter survival time, and combinatorial expression of these 3 genes was an independent predictor for survival. The downstream target genes for TAZ-AXL-CTGF overexpression were identified by Java application MyStats. Interestingly, genes that are associated with colon cancer progression (ANTXR1, EFEMP2, SULF1, TAGLN, VCAN, ZEB1 and ZEB2) were upregulated in patients co-overexpressing TAZ-AXL-CTGF. This TAZ-AXL-CTGF gene expression signature (GES) was then applied to Connectivity Map to identify small molecules that could potentially be utilized to reverse this GES. Of the top 20 small molecules identified by connectivity map, amiloride (a potassium sparing diuretic,) and tretinoin (all-trans retinoic acid) have shown therapeutic promise in inhibition of colon cancer cell growth. Using MyStats, we found that low level expression of either ANO1 or SQLE were associated with a better prognosis in patients who co-overexpressed TAZ-AXL-CTGF, and that ANO1 was an independent predictor of survival together with TAZ-AXL-CTGF. Finally, we confirmed that TAZ regulates Axl, and plays an important role in clonogenicity and non-adherent growth in vitro and tumor formation in vivo. These data suggest that TAZ could be a therapeutic target for the treatment of colon cancer

A collation of data on European flash floods

Flash floods are one of the most significant natural hazards in Europe, causing serious risk to life and destruction of buildings and infrastructure. This type of flood, often affecting ungauged watersheds, remains nevertheless a poorly documented phenomenon. To address the gap in available information, and particularly to assess the possible ranges for peak discharges on watersheds with area smaller than 500 km2 and to describe the geography of the hazard across Europe, an intensive data compilation has been carried out for seven European hydrometeorological regions. This inventory is the first step towards an atlas of extreme flash floods in Europe. It contains over 550 documented events. This paper aims at presenting the data compilation strategy, the content of the elaborated data base and some preliminary data analysis results. The initial observations show that the most extreme flash floods are greater in magnitude in the Mediterranean countries than in the inner continental countries and that there is a strong seasonality to flash flood occurrence revealing different climatic forcing mechanisms in each region