Multi-sensor background subtraction by fusing multiple region-based probabilistic classifiers

In the recent years, the computer vision community has shown great interest on depth-based applications thanks to the performance and flexibility of the new generation of RGB-D imagery. In this paper, we present an efficient background subtraction algorithm based on the fusion of multiple region-based classifiers that processes depth and color data provided by RGB-D cameras. Foreground objects are detected by combining a region-based foreground prediction (based on depth data) with different background models (based on a Mixture of Gaussian algorithm) providing color and depth descriptions of the scene at pixel and region level. The information given by these modules is fused in a mixture of experts fashion to improve the foreground detection accuracy. The main contributions of the paper are the region-based models of both background and foreground, built from the depth and color data. The obtained results using different database sequences demonstrate that the proposed approach leads to a higher detection accuracy with respect to existing state-of-the-art techniques.

Forest products market in Spain 2015: situation and projections

The Spanish economy is slightly showing positive recovery signs. Construction figures and domestic consumption, which are the most relevant market drivers for forest products, are also significantly better than in the last years. This article analyzes the projections for 2015 in several forest products markets. The conclusion is that a certain general improvement can be expected in most of them, though showing different figures and values.

Class-Conditional Probabilistic Principal Component Analysis: application to gender recognition

Este trabajo presenta una solución al problema del reconocimiento del género de un rostro humano a partir de una imagen. Adoptamos una aproximación que utiliza la cara completa a través de la textura de la cara normalizada y redimensionada como entrada a un clasificador Näive Bayes. Presentamos la técnica de Análisis de Componentes Principales Probabilístico Condicionado-a-la-Clase (CC-PPCA) para reducir la dimensionalidad de los vectores de características para la clasificación y asegurar la asunción de independencia para el clasificador. Esta nueva aproximación tiene la deseable propiedad de presentar un modelo paramétrico sencillo para las marginales. Además, este modelo puede estimarse con muy pocos datos. En los experimentos que hemos desarrollados mostramos que CC-PPCA obtiene un 90% de acierto en la clasificación, resultado muy similar al mejor presentado en la literatura---ABSTRACT---This paper presents a solution to the problem of recognizing the gender of a human face from an image. We adopt a holistic approach by using the cropped and normalized texture of the face as input to a Naïve Bayes classifier. First it is introduced the Class-Conditional Probabilistic Principal Component Analysis (CC-PPCA) technique to reduce the dimensionality of the classification attribute vector and enforce the independence assumption of the classifier. This new approach has the desirable property of a simple parametric model for the marginals. Moreover this model can be estimated with very few data. In the experiments conducted we show that using CCPPCA we get 90% classification accuracy, which is similar result to the best in the literature. The proposed method is very simple to train and implement.

A methodology to estimate uncertainty for emission projections through sensitivity analysis

Air pollution abatement policies must be based on quantitative information on current and future emissions of pollutants. As emission projections uncertainties are inevitable and traditional statistical treatments of uncertainty are highly time/resources consuming, a simplified methodology for nonstatistical uncertainty estimation based on sensitivity analysis is presented in this work. The methodology was applied to the “with measures” scenario for Spain, concretely over the 12 highest emitting sectors regarding greenhouse gas and air pollutants emissions. Examples of methodology application for two important sectors (power plants, and agriculture and livestock) are shown and explained in depth. Uncertainty bands were obtained up to 2020 by modifying the driving factors of the 12 selected sectors and the methodology was tested against a recomputed emission trend in a low economic-growth perspective and official figures for 2010, showing a very good performance. Implications: A solid understanding and quantification of uncertainties related to atmospheric emission inventories and projections provide useful information for policy negotiations. However, as many of those uncertainties are irreducible, there is an interest on how they could be managed in order to derive robust policy conclusions. Taking this into account, a method developed to use sensitivity analysis as a source of information to derive nonstatistical uncertainty bands for emission projections is presented and applied to Spain. This method simplifies uncertainty assessment and allows other countries to take advantage of their sensitivity analyses.

Segment-specific pattern of sympathetic preganglionic projections in the chicken embryo spinal cord is altered by retinoids

Sympathetic preganglionic neurons exhibit segment-specific projections. Preganglionic neurons located in rostral spinal segments project rostrally within the sympathetic chain, those located in caudal spinal segments project caudally, and those in midthoracic segments project either rostrally or caudally in segmentally graded proportions. Moreover, rostrally and caudally projecting preganglionic neurons are skewed toward the rostral and caudal regions, respectively, of each midthoracic segment. The mechanisms that establish these segment-specific projections are unknown. Here we show that experimental manipulation of retinoid signaling in the chicken embryo alters the segment-specific pattern of sympathetic preganglionic projections and that this effect is mediated by the somitic mesoderm. Application of exogenous retinoic acid to a single rostral thoracic somite decreases the number of rostrally projecting preganglionic neurons at that level. Conversely, disrupting endogenous synthesis of retinoic acid in a single caudal thoracic somite increases the number of rostrally projecting preganglionic neurons at that level. The number of caudally projecting neurons does not change in either case, indicating that the effect is specific for rostrally projecting preganglionic neurons. These results indicate that the sizes of the rostrally and caudally projecting populations may be independently regulated by different factors. Opposing gradients of such factors along the longitudinal axis of the thoracic region of the embryo could be sufficient, in combination, to determine the segment-specific identity of preganglionic projections.

The effects of health changes on projections of health service needs for the elderly population of the United States

The 1982–1994 National Long-Term Care Surveys indicate an accelerating decline in disability among the U.S. elderly population, suggesting that a 1.5% annual decline in chronic disability for elderly persons is achievable. Furthermore, many risk factors for chronic diseases show improvements, many linked to education, from 1910 to the present. Projections indicate the proportion of persons aged 85–89 with less than 8 years of education will decline from 65% in 1980 to 15% in 2015. Health and socioeconomic status trends are not directly represented in Medicare Trust Fund and Social Security Administration beneficiary projections. Thus, they may have different economic implications from projections directly accounting for health trends. A 1.5% annual disability decline keeps the support ratio (ratio of economically active persons aged 20–64 to the number of chronically disabled persons aged 65+) above its 1994 value, 22:1, when the Hospital Insurance Trust Fund was in fiscal balance, to 2070. With no changes in disability, projections indicate a support ratio in 2070 of 8:1—63% below a cash flow balance.

GABAergic feedforward projections from the inferior colliculus to the medial geniculate body.

A novel and robust projection from gamma-aminobutyric acid-containing (GABAergic) inferior colliculus neurons to the media] geniculate body (MGB) was discovered in the cat using axoplasmic transport methods combined with immunocytochemistry. This input travels with the classical inferior colliculus projection to the MGB, and it is a direct ascending GABAergic pathway to the sensory thalamus that may be inhibitory. This bilateral projection constitutes 10-30% of the neurons in the auditory tectothalamic system. Studies by others have shown that comparable input to the corresponding thalamic visual or somesthetic nuclei is absent. This suggests that monosynaptic inhibition or disinhibition is a prominent feature in the MGB and that differences in neural circuitry distinguish it from its thalamic visual and somesthetic counterparts.

The impact of a future solar minimum on climate change projections in the Northern Hemisphere

Solar variability represents a source of uncertainty in the future forcings used in climate model simulations. Current knowledge indicates that a descent of solar activity into an extended minimum state is a possible scenario. With aid of experiments from a state-of-the-art Earth system model, we investigate the impact of a future solar minimum on Northern Hemisphere climate change projections. This scenario is constructed from recent 11 year solar-cycle minima of the solar spectral irradiance, and is therefore more conservative than the 'grand' minima employed in some previous modeling studies. Despite the small reduction in total solar irradiance (0.36 W m^-2), relatively large responses emerge in the winter Northern Hemisphere, with a reduction in regional-scale projected warming by up to 40%. To identify the origin of the enhanced regional signals, we assess the role of the different mechanisms by performing additional experiments forced only by irradiance changes at different wavelengths of the solar spectrum. We find that a reduction in visible irradiance drives changes in the stationary wave pattern of the North Pacific and sea-ice cover. A decrease in UV irradiance leads to smaller surface signals, although its regional effects are not negligible. These results point to a distinct but additive role of UV and visible irradiance in the Earth's climate, and stress the need to account for solar forcing as a source of uncertainty in regional scale projections.

A combined probabilistic framework for learning gestures and actions

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the core of tracking and recognition of gestures and tasks. We describe the overall architecture of the system and detail learning processes and gesture design. Finally we show experimental results of tracking and recognition in block-world like assembling tasks and in general human gestures.

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.

Behaviours, Processes and Probabilistic Environmental Functions in H-Open Systems

The Patten’s Theory of the Environment, supposes an impotent contribution to the Theoretical Ecology. The hypothesis of the duality of environments, the creaon and genon functions and the three developed propositions are so much of great importance in the field of the Applied Mathematical as Ecology. The authors have undertaken an amplification and revision of this theory, developing the following steps: 1) A theory of processes. 2) A definition of structural and behavioural functions. 3) A probabilistic definition of the environmental functions. In this paper the authors develop the theory of behavioural functions, begin the theory of environmental functions and give a complementary focus to the theory of processes that has been developed in precedent papers.

A Quantile-Based Probabilistic Mean Value Theorem

For non-negative random variables with finite means we introduce an analogous of the equilibrium residual-lifetime distribution based on the quantile function. This allows us to construct new distributions with support (0, 1), and to obtain a new quantile-based version of the probabilistic generalization of Taylor's theorem. Similarly, for pairs of stochastically ordered random variables we come to a new quantile-based form of the probabilistic mean value theorem. The latter involves a distribution that generalizes the Lorenz curve. We investigate the special case of proportional quantile functions and apply the given results to various models based on classes of distributions and measures of risk theory. Motivated by some stochastic comparisons, we also introduce the “expected reversed proportional shortfall order”, and a new characterization of random lifetimes involving the reversed hazard rate function.

On the Result of Invariance of the Closure Set of the Real Projections of the Zeros of an Important Class of Exponential Polynomials

In this paper we provide the proof of a practical point-wise characterization of the set RP defined by the closure set of the real projections of the zeros of an exponential polynomial P(z) = Σn j=1 cjewjz with real frequencies wj linearly independent over the rationals. As a consequence, we give a complete description of the set RP and prove its invariance with respect to the moduli of the c′ js, which allows us to determine exactly the gaps of RP and the extremes of the critical interval of P(z) by solving inequations with positive real numbers. Finally, we analyse the converse of this result of invariance.