44 resultados para Spatio-temporal model

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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We propose a spatio-temporal rich model of motion vector planes as a part of a full steganalytic system against motion vector based steganography. Superior detection accuracy of the rich model over the previous methods has been lately demonstrated for digital images in both spatial and DCT domain. It has not been heretofore used for detection of motion vector steganography. We also introduced a transformation so as to extend the feature set with temporal residuals. We carried out the tests along with most recent motion vector steganalysis and steganography methods. Test results show that the proposed model delivers an outstanding performance compared to the previous methods.

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A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.

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This paper addresses the pose recovery problem of a particular articulated object: the human body. In this model-based approach, the 2D-shape is associated to the corresponding stick figure allowing the joint segmentation and pose recovery of the subject observed in the scene. The main disadvantage of 2D-models is their restriction to the viewpoint. To cope with this limitation, local spatio-temporal 2D-models corresponding to many views of the same sequences are trained, concatenated and sorted in a global framework. Temporal and spatial constraints are then considered to build the probabilistic transition matrix (PTM) that gives a frame to frame estimation of the most probable local models to use during the fitting procedure, thus limiting the feature space. This approach takes advantage of 3D information avoiding the use of a complex 3D human model. The experiments carried out on both indoor and outdoor sequences have demonstrated the ability of this approach to adequately segment pedestrians and estimate their poses independently of the direction of motion during the sequence. (c) 2008 Elsevier Ltd. All rights reserved.

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The crowned sifaka (Propithecus coronatus) and Decken’s sifaka (Propithecus deckenii) are Endangered lemurs endemic to west and central Madagascar. Both have suffered habitat loss and fragmentation throughout their ranges. The goal
of this study, conducted in the Mahavavy-Kinkony Wetland Complex (MKWC) in northwestern Madagascar, was to assess the effects of historical change in the species’ habitats, and to model the potential impact of further land-use change on their habitats. The IDRISI Andes Geographical Information System and image-processing software was used for satellite-image classifiation, and the Land Change Modeler was used to compare the natural habitat of the species from 1973 to 2005, and to predict available habitat for 2050. We analyzed two forests in the MKWC occupied by P. coronatus (Antsilaiza and Anjohibe), and three forests occupied by P. deckenii (Tsiombikibo, Marofandroboka and Andohaomby). The two forests occupied by P. coronatus contracted during the period 1949–1973, but then expanded to exceed their 1949 area by 28% in 2005. However, the land change model predicted that they will contract again to match their 1949 area by 2050, and will again lose their corridor connection, meaning that the conservation gains for this species in the complex are at risk of being reversed. The three forests occupied by P. deckenii have declined in area steadily since 1949, losing 20% of their original area by 2005, and are predicted to lose a further 15% of their original area by 2050. Both species are therefore at risk of becoming even more threatened if land-use change continues within the complex. Improved conservation of the remaining forest is recommended to avoid further loss, as well as ecological restoration and reforestation to promote connectivity between the forests. A new strategy for controlling agriculture and forest use is required in order to avoid further destruction of the forest.

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Several countries have made large investments in building historical Geographical Information Systems (GIS) databases containing census and other quantitative statistics over long periods of time. Making good use of these databases requires approaches that explore spatial and temporal change.

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Cellular response to radiation damage is made by a complex network of pathways and feedback loops whose spatiotemporal organization is still unclear despite its decisive role in determining the fate of the damaged cell. The single-cell approach and the high spatial resolution offered by microbeams provide the perfect tool to study and quantify the dynamic processes associated with the induction and repair of DNA damage. The soft X-ray microbeam has been used to follow the development of radiation induced foci in live cells by monitoring their size and intensity as a function of dose and time using yellow fluorescent protein (YFP) tagging techniques. Preliminary data indicate a delayed and linear rising of the intensity signal indicating a slow kinetic for the accumulation of DNA repair protein 53BP1. A slow and limited foci diffusion has also been observed. Further investigations are required to assess whatever such diffusion is consistent with a random walk pattern or if it is the result of a more structured lesion processing phenomenon. In conclusion, our data indicates that the use of microbeams coupled to live cell microscopy represent a sophisticated approach for visualizing and quantifying the dynamics changes of DNA proteins at the damaged sites.

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We investigated groundwater salinity as a key element in both the short and long-term evolution of the island of Grande Glorieuse. Firstly, we demonstrated that its evolution involved the integration of the whole range of variables forcing climate change. Piezometric surveys designed to sample the salinity of the subsoil waters of Grande Glorieuse could therefore provide an objective indicator of the environment’s evolution. Then, based on information from geoelectrical investigations, we proved that the spatial distribution of salinity is strongly dependent on the geological structure of the island. Structural heterogeneities can influence vulnerability of the island environment to salinization of the freshwater lens. Thus, characterization and monitoring of the freshwater lens will provide a reliable means of observing and managing anticipated climate changes on small islands. [Join J.-L., Banton O., Comte J.-C., Leze J., Massin F., Nicolini E. (2011), Assessing spatio-temporal patterns of groundwater salinity in small coral islands in the Western Indian Ocean, Western Indian Ocean Journal of Marine Science, 10(1), 1-12]

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We present a Spatio-temporal 2D Models Framework (STMF) for 2D-Pose tracking. Space and time are discretized and a mixture of probabilistic "local models" is learnt associating 2D Shapes and 2D Stick Figures. Those spatio-temporal models generalize well for a particular viewpoint and state of the tracked action but some spatio-temporal discontinuities can appear along a sequence, as a direct consequence of the discretization. To overcome the problem, we propose to apply a Rao-Blackwellized Particle Filter (RBPF) in the 2D-Pose eigenspace, thus interpolating unseen data between view-based clusters. The fitness to the images of the predicted 2D-Poses is evaluated combining our STMF with spatio-temporal constraints. A robust, fast and smooth human motion tracker is obtained by tracking only the few most important dimensions of the state space and by refining deterministically with our STMF.

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Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

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Aim: Impacts of invasive species may vary across invasion gradients, owing to trait-based sorting of individuals through dispersal: those aggregating at invasion fronts may be more aggressive and voracious. We examine, in the field and laboratory, variation in the predatory impacts of an invasive Ponto-Caspian crustacean Hemimysis anomala G.O. Sars, 1907 at two sites along a spatio-temporal gradient of invasion.

Location: Republic of Ireland.

Methods: We used reciprocal transplant field-deployed mesocosms to compare predation rates of invasion front and well-established H. anomala on natural zooplankton assemblages. In the laboratory, we measured the functional response (relationship between predation rate and prey supply) of H. anomala from both sites, for a per capita mechanistic comparison of predation efficiency. We also assessed prey selectivity of H. anomala in the mesocosm experiments to further compare feeding behaviour. Finally, we used a correlative approach to assess the community impact of H. anomala across sites, including a nearby uninvaded site, by comparing zooplankton diversities and densities.

Results: Invasion front H. anomala had higher predation rates than well-established H. anomala at high in situ zooplankton densities. Invasion front H. anomala also had higher functional responses - in particular showing higher 'attack rates' - indicating a heightened ability to locate and capture prey. Prey selectivity was consistent across the spatio-temporal contrast, with positive selection for cladocerans. Zooplankton diversity and density declined with time since H. anomala invasion, both being maximal at the uninvaded site.

Main conclusions: Our study, for the first time, (1) reveals differences in predatory per capita effects and associated behavioural traits between two sites along a spatio-temporal invasion gradient and (2) shows a negative community-level impact of the invasive H. anomala in natural water bodies. Further spatio-temporal comparisons of predatory per capita effects of invaders are needed to assess the generality of these results.

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Understanding the dietary consumption and selection of wild populations of generalist herbivores is hampered by the complex array of factors. Here, we determine the influence of habitat, season, and animal density, sex, and age on the diet consumption and selection of 426 red deer (Cervus elaphus scoticus) culled in Fiordland National Park, New Zealand. Our site differs from studies elsewhere both in habitat (evergreen angiosperm-dominated forests) and the intensity of hunting pressures. We predicted that deer would not consume forage in proportion to its relative availability, and that dietary consumption would change among and within years in response to hunting pressures that would also limit opportunities for age and sex segregation. Using canonical correspondence analysis, we evaluated the relative importance of different drivers of variation in diet consumption assessed from gut content and related these to available forage in the environment. We found that altitude explained the largest proportion of variation in diet consumption, reflecting the ability of deer to alter their consumption and selection in relation to their foraging grounds. Grasses formed a high proportion of the diet consumption, even for deer culled several kilometres from the alpine grasslands. In the winter months, when the alpine grasslands were largely inaccessible, less grass was eaten and deer resorted to woody plants that were avoided in the summer months. Surprisingly, there were no significant dietary differences between adults and juveniles and only subtle differences between the sexes. Sex-based differences in diet consumption are commonly observed in ungulate species and we suggest that they may have been reduced in our study area owing to decreased heterogeneity in available forage as the diversity of palatable species decreased under high deer browsing pressures, or by intense hunting pressure. © 2009 The Authors. Journal compilation © 2009 Ecological Society of Australia.

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The last decade has witnessed an unprecedented growth in availability of data having spatio-temporal characteristics. Given the scale and richness of such data, finding spatio-temporal patterns that demonstrate significantly different behavior from their neighbors could be of interest for various application scenarios such as – weather modeling, analyzing spread of disease outbreaks, monitoring traffic congestions, and so on. In this paper, we propose an automated approach of exploring and discovering such anomalous patterns irrespective of the underlying domain from which the data is recovered. Our approach differs significantly from traditional methods of spatial outlier detection, and employs two phases – i) discovering homogeneous regions, and ii) evaluating these regions as anomalies based on their statistical difference from a generalized neighborhood. We evaluate the quality of our approach and distinguish it from existing techniques via an extensive experimental evaluation.