De la détection d'évènements sonores violents par SVM dans les films

National audienceThis article studies the behaviour of a state-of-the-art support vector machine audio event detection approach, applied to violent event detection in movies. The events we are trying to detect are screams, gunshots, explosions. Contrary to others studies, we show that the state-of-theart approach does not lead to good results on this task. A study on the repartition of samples into subsets in a cross validation protocol helps explain those results and highlights a generalisation problem due to a polymorphism of considered classes. This polymorphism is demonstrated by the computation the divergence between the samples of the test database and the training database.Cet article étudie le comportement d'une approche classique, à l'état de l'art, pour la détection d'événements sonores par machines à vecteurs supports, appliquée à la détection d'événements violents dans les films. Les événements sonores considérés, liés à la présence de violence, sont les Cris, les Coups de feu et les Explosions. Nous montrons que, contrairement aux résultats d'autres études, l'approche état de l'art ne donne pas de bons résultats sur cette tâche. Une étude sur la répartition des échantillons en sous-ensembles dans un protocole de validation croisée permet d'expliquer ces résultats et met en évidence un problème de généralisation, dû au polymorphisme des classes considérées. Ce polymorphisme est démontré par un calcul de divergence entre les échantillons de la base de test et ceux de la base d'apprentissage

Audio Event Detection in Movies using Multiple Audio Words and Contextual Bayesian Networks

International audienceThis article investigates a novel use of the well known audio words representations to detect specific audio events, namely gunshots and explosions, in order to get more robustness towards soundtrack variability in Hollywood movies. An audio stream is processed as a sequence of stationary segments. Each segment is described by one or several audio words obtained by applying product quantization to standard features. Such a representation using multiple audio words constructed via product quantisation is one of the novelties described in this work. Based on this representation, Bayesian networks are used to exploit the contextual information in order to detect audio events. Experiments are performed on a comprehensive set of 15 movies, made publicly available. Results are comparable to the state of the art results obtained on the same dataset but show increased robustness to decision thresholds, however limiting the range of possible operating points in some conditions. Late fusion provides a solution to this issue

MediaEval 2017 Predicting Media Interestingness Task

Non peer reviewe

Reconstitution of a Continuous Climatic and Rainfall Series for the Central Sahel (1950-2012): Data, Methodology and Application

The Sahel is one of the regions in the world which has experienced the strongest climatic changes in the past decades. In a context of high population growth and mainly agriculture-based economies and livelihoods, these fluctuations can cause serious societal problems. Understanding past and predicting future climatic changes and their implications on natural and cultivated ecosystems are henceprimordial. Modelling efforts in the fields of hydrology and ecohydrology have already been undertaken, but are hindered by data availability as soon as the multi-decadal time scale is targeted. Indeed, in addition to being scarce, climatic data are often discontinuous in time, limiting the use of many modelling tools. In this study we produced a continuous and consistent data set at Niamey, Niger (13.5° N, 2.1° E) from 1950 to 2012 at different temporal scales (daily, 3-h and 30-min) that can be used as inputs in most LSM-type, vegetation and hydrological models. A stochastic component was introduced to reflect the uncertainty on the determination of missing data. Variables under study were: rainfall, air temperature, specific humidity, air pressure, wind speed, cloud cover, clear-sky longwave and shortwave radiation. Missing data were filled through regression methods, artificial neural networks, or by randomly selecting the missing variables from data classes presenting similar properties. The datasets showed an increase in temperature of over 1°C since the 1950s. They also maintained the diurnal and seasonal cycles for all variables, thus verifying their internal coherence. Uncertainty at the sub-daily scale did not propagate at longer time-scales for the climatic data. Finally, trends in the seasonal and diurnal cycle of main variables were analyzed and were found coherent with published data. As an illustration of a possible use of this dataset, variations in the water and energy budgets for 1950-2012 for a major ecosystem in the region were simulated using a detailed LSM/SVAT model (SiSPAT). This dataset could be used by the community to better understand and predict land-surface-atmosphere interactions in Central Sahel, including hydrological ones, such as historical changes in yield, growth of natural vegetation, changes in the water cycle and as a high-quality baseline for climate change impacts studies

MediaEval 2016 Predicting Media Interestingness Task

Volume: 1739 Host publication title: MediaEval 2016 Multimedia Benchmark Workshop Host publication sub-title: Working Notes Proceedings of the MediaEval 2016 WorkshopNon peer reviewe

Production de carbone organique dissous par le complexe macrophytes-épiphytes : effets de facteurs physico-chimiques, implications sur la productivité des communautés de macrophytes et incidence à l'échelle de l'écosystème

Cette thèse ne contient pas de résumé

Observed long-term land cover vs climate impacts on the West African hydrological cycle: lessons for the future ? [P-3330-65]

West Africa has experienced a long lasting, severe drought as from 1970, which seems to be attenuating since 2000. It has induced major changes in living conditions and resources over the region. In the same period, marked changes of land use and land cover have been observed: land clearing for agriculture, driven by high demographic growth rates, and ecosystem evolutions driven by the rainfall deficit. Depending on the region, the combined effects of these climate and environmental changes have induced contrasted impacts on the hydrological cycle. In the Sahel, runoff and river discharges have increased despite the rainfall reduction (“less rain, more water”, the so-called "Sahelian paradox "). Soil crusting and erosion have increased the runoff capacity of the watersheds so that it outperformed the rainfall deficit. Conversely, in the more humid Guinean and Sudanian regions to the South, the opposite (and expected) “less rain, less water” behavior is observed, but the signature of land cover changes can hardly be detected in the hydrological records. These observations over the past 50 years suggest that the hydrological response to climate change can not be analyzed irrespective of other concurrent changes, and primarily ecosystem dynamics and land cover changes. There is no consensus on future rainfall trend over West Africa in IPCC projections, although a higher occurrence of extreme events (rainstorms, dry spells) is expected. An increase in the need for arable land and water resources is expected as well, driven by economic development and demographic growth. Based on past long-term observations on the AMMA-CATCH observatory, we explore in this work various future combinations of climate vs environmental drivers, and we infer the expected resulting trends on water resources, along the west African eco-climatic gradient. (Texte intégral

Observed long-term land cover vs climate impacts on the West African hydrological cycle: lessons for the future ? [P-3330-65]

West Africa has experienced a long lasting, severe drought as from 1970, which seems to be attenuating since 2000. It has induced major changes in living conditions and resources over the region. In the same period, marked changes of land use and land cover have been observed: land clearing for agriculture, driven by high demographic growth rates, and ecosystem evolutions driven by the rainfall deficit. Depending on the region, the combined effects of these climate and environmental changes have induced contrasted impacts on the hydrological cycle. In the Sahel, runoff and river discharges have increased despite the rainfall reduction (“less rain, more water”, the so-called "Sahelian paradox "). Soil crusting and erosion have increased the runoff capacity of the watersheds so that it outperformed the rainfall deficit. Conversely, in the more humid Guinean and Sudanian regions to the South, the opposite (and expected) “less rain, less water” behavior is observed, but the signature of land cover changes can hardly be detected in the hydrological records. These observations over the past 50 years suggest that the hydrological response to climate change can not be analyzed irrespective of other concurrent changes, and primarily ecosystem dynamics and land cover changes. There is no consensus on future rainfall trend over West Africa in IPCC projections, although a higher occurrence of extreme events (rainstorms, dry spells) is expected. An increase in the need for arable land and water resources is expected as well, driven by economic development and demographic growth. Based on past long-term observations on the AMMA-CATCH observatory, we explore in this work various future combinations of climate vs environmental drivers, and we infer the expected resulting trends on water resources, along the west African eco-climatic gradient. (Texte intégral

Modélisation cohérente de la diffusion électromagnétique par des surfaces de mer tridimensionnelles en incidence rasante.: Application aux radars HF à ondes de surface.

This thesis deals with the analysis of the electromagnetic interactions between surface waves at HF frequencies, and a time-evolving sea surface. A simulator comprising three specific elements has been developed.The first one enables the user to model a time-varying sea surface in three dimensions, by the application of the linear wave theory. The second one simulates the interaction between the electromagnetic wave at grazing incidence and the sea surface using an exact model based on the method of moments. Lastly, a post-processing tool allows the plotting and the analysis of the resulting Doppler spectra. Validation tests are presented. Various simulations on static and dynamic surfaces (sinusoids and sea surfaces) reveal the Bragg resonance phenomenon and the Doppler effect respectively. The influence of the sea surface and the radar configuration is investigated. The simulation results show a good fit with published data and ONERA measurements. Finally, a film of pollutant on the surface is introduced in the model by the addition of a surface pressure (corresponding here to an attenuation of the heights of the waves). The effect of the presence of the film on the Doppler spectra is analyzed.Cette thèse repose sur l'analyse des interactions électromagnétiques (EM) entre les ondes de surface, aux fréquences HF, et une surface de mer évoluant dans le temps. Un simulateur comprenant trois modules spécifiques est développé. Le premier élément permet de modéliser une surface de mer en 3D variant dans le temps, par application de la théorie linéaire des vagues. Le second fait interagir une onde EM en incidence rasante avec une surface de mer grâce à un modèle exact qui s'appuie sur la méthode des moments. Enfin, un outil de post-traitement offre la possibilité de tracer et d'analyser des spectres Doppler (SD) résultants. Une étude portant sur des surfaces statiques puis dynamiques est menée. Elle fait apparaître respectivement le phénomène de résonance de Bragg et l'effet Doppler. Des données déjà publiées ou mesurées indiquent une bonne adéquation avec les SD simulés. Finalement, l'effet sur les SD, de la présence d'un film de polluant sur la surface de mer, est analysé

Annotating, Understanding, and Predicting Long-term Video Memorability

International audienceMemorability can be regarded as a useful metric of video importance to help make a choice between competing videos. Research on computational understanding of video memorability is however in its early stages. There is no available dataset for modelling purposes, and the few previous attempts provided protocols to collect video memorability data that would be difficult to generalize. Furthermore, the computational features needed to build a robust memorability predictor remain largely undiscovered. In this article, we propose a new protocol to collect long-term video memorability annotations. We measure the memory performances of 104 participants from weeks to years after memorization to build a dataset of 660 videos for video memorability prediction. This dataset is made available for the research community. We then analyze the collected data in order to better understand video memorability, in particular the effects of response time, duration of memory retention and repetition of visualization on video memorability. We finally investigate the use of various types of audio and visual features and build a computational model for video memorability prediction. We conclude that high level visual semantics help better predict the memorability of videos