Kernel bandwidth estimation for moving object detection in non-stabilized cameras

The evolution of the television market is led by 3DTV technology, and this tendency can accelerate during the next years according to expert forecasts. However, 3DTV delivery by broadcast networks is not currently developed enough, and acts as a bottleneck for the complete deployment of the technology. Thus, increasing interest is dedicated to ste-reo 3DTV formats compatible with current HDTV video equipment and infrastructure, as they may greatly encourage 3D acceptance. In this paper, different subsampling schemes for HDTV compatible transmission of both progressive and interlaced stereo 3DTV are studied and compared. The frequency characteristics and preserved frequency content of each scheme are analyzed, and a simple interpolation filter is specially designed. Finally, the advantages and disadvantages of the different schemes and filters are evaluated through quality testing on several progressive and interlaced video sequences

Historia literaria de España, desde su primera población hasta nuestros dias ...

Copia digital : Diputación Provincial de Zaragoza. Servicio de Archivos y Bibliotecas, 2010Sign.: [ ]\p4\s, A-Z\p4\s, 2A-2P\p4\sAntep

Statistical moving object detection for mobile devices with camera

A novel and high-quality system for moving object detection in sequences recorded with moving cameras is proposed. This system is based on the collaboration between an automatic homography estimation module for image alignment, and a robust moving object detection using an efficient spatiotemporal nonparametric background modeling

Versatile Bayesian classifier for moving object detection by non-parametric background-foreground modeling

Along the recent years, several moving object detection strategies by non-parametric background-foreground modeling have been proposed. To combine both models and to obtain the probability of a pixel to belong to the foreground, these strategies make use of Bayesian classifiers. However, these classifiers do not allow to take advantage of additional prior information at different pixels. So, we propose a novel and efficient alternative Bayesian classifier that is suitable for this kind of strategies and that allows the use of whatever prior information. Additionally, we present an effective method to dynamically estimate prior probability from the result of a particle filter-based tracking strategy

Adaptable Bayesian classifier for spatiotemporal nonparametric moving object detection strategies

Electronic devices endowed with camera platforms require new and powerful machine vision applications, which commonly include moving object detection strategies. To obtain high-quality results, the most recent strategies estimate nonparametrically background and foreground models and combine them by means of a Bayesian classifier. However, typical classifiers are limited by the use of constant prior values and they do not allow the inclusion of additional spatiodependent prior information. In this Letter, we propose an alternative Bayesian classifier that, unlike those reported before, allows the use of additional prior information obtained from any source and depending on the spatial position of each pixel

N-doped activated carbon as support of Pd-Sn bimetallic catalysts for nitrate catalytic reduction

This work studies the catalytic reduction of nitrate using N-doped activated carbon catalysts. Activated carbons were prepared by hydrothermal carbonization (220 °C, 80 % water, 16 h) of garden and park waste and olive stones using (NH4)2SO4 as N source, followed by chemical activation with H3PO4 at 500 °C (N2 atmosphere, 1 h). These were impregnated with Pd and Sn to prepare bimetallic catalysts for nitrate catalytic reduction. N-doping improved the BET surface area up to 1369 m2 g−1 and increased the N content on the catalyst surface to 3 wt%. The N-doped catalysts showed better catalytic performance than the non-doped ones, showing high stability for 100 h on stream, reaching even higher activity than a catalyst supported on a commercial activated carbon. N-doping also showed a positive effect by decreasing NH4+ selectivity. Finally, natural and drinking waters spiked with NO3- were treated in continuous flow, exhibiting the N-doped activated carbon catalysts, prepared from garden and park waste, a high tolerance to ions other than NO3- present in the water solutionThe authors greatly appreciate the financial support from the Spanish MICINN (PID 2019-108445RB-100), Comunidad de Madrid (S2018/ EMT-4344). I. Sanchis wishes to thank the Comunidad de Madrid for PEJD-2017-PRE/AMB-4616 contrac

Cation and anion effect on the biodegradability and toxicity of imidazolium-and choline-based ionic liquids

This work studies the effect of the cation and anion on the biodegradability and inhibition of imidazolium- and choline-based ionic liquids (ILs) using activated sludge. Six commercial ILs, formed by combination of 1-Butyl-3-methylimidazolium (Bmim+) and N,N,N-trimethylethanolammonium (Choline+) cations and chloride (Cl-), acetate (Ac-) and bis(trifluoromethanesulfonyl)imide (NTf2-) anions were evaluated, all representative counter-ions with markedly different toxicity and biodegradability. Inherent and fast biodegradability tests were used to evaluate both the microorganism inhibition and the IL biodegradability. In addition, the ecotoxicological response (EC50) of the ILs was studied using activated sludge and Vibrio fischeri (Microtox® test). Bmim+ and NTf2- can be considered as non-biodegradable, whereas aerobic microorganisms easily degraded Choline+ and Ac-. The biodegradation pattern of each cation/anion is nearly unaffected by counter-ion nature. Moreover, concentrations of CholineNTf2 higher than 50 mg/L caused a partial inhibition on microbial activity, in good concordance with its low EC50 (54 mg/L) measured by respiration inhibition test, which alerts on the negative environmental impact of NTf2-containing ILs on the performance of sewage treatment plantsThe authors greatly appreciate financial support from the Spanish MINECO (CTM2016–76564–R), Comunidad de Madrid (BIOTRES–CM, S2018/EMT–4344), and UAM–Santander (CEAL–AL/2015–08). I.F. Mena wishes to thank the MINECO and the ESF for a research grant (BES–2014–069986). The valuable contribution of J. Lemus is also acknowledge

On the Mahalanobis Distance Classification Criterion for Multidimensional Normal Distributions

Many existing engineering works model the statistical characteristics of the entities under study as normal distributions. These models are eventually used for decision making, requiring in practice the definition of the classification region corresponding to the desired confidence level. Surprisingly enough, however, a great amount of computer vision works using multidimensional normal models leave unspecified or fail to establish correct confidence regions due to misconceptions on the features of Gaussian functions or to wrong analogies with the unidimensional case. The resulting regions incur in deviations that can be unacceptable in high-dimensional models. Here we provide a comprehensive derivation of the optimal confidence regions for multivariate normal distributions of arbitrary dimensionality. To this end, firstly we derive the condition for region optimality of general continuous multidimensional distributions, and then we apply it to the widespread case of the normal probability density function. The obtained results are used to analyze the confidence error incurred by previous works related to vision research, showing that deviations caused by wrong regions may turn into unacceptable as dimensionality increases. To support the theoretical analysis, a quantitative example in the context of moving object detection by means of background modeling is given

Effect of water composition on catalytic reduction of nitrate

This work studies catalytic reduction of nitrate with bimetallic catalysts supported on γ-alumina (Pd-Sn/Al2O3 and Pd-In/Al2O3). Pd-Sn/Al2O3 yielded higher NO3− conversion and selectivity towards N2 than Pd-In/Al2O3 in synthetic water (deionized water with 100 mg/L NO3−). The Pd-Sn/Al2O3 catalyst showed highly stable behaviour, without signs of deactivation upon ten consecutive runs of 6 h each, where almost equal low selectivity to NH4+ (absence of NO2−) was maintained at high nearly constant nitrate conversion (≈ 90%). The presence of anions (Cl−, SO42− and HCO3−) in the reaction medium decreased NO3− conversion and the selectivity towards N2. Chloride showed a moderately negative effect at relatively low concentration. The effect of SO42− and HCO3− was more pronounced, being the second the most detrimental to the catalytic activity. The selectivity towards N2 was also negatively affected by the presence of those anions following the sequence HCO3− > SO42− > Cl−. However, the joint presence of Cl− or SO42− with HCO3− reduced the negative effect of the latter. The Pd-Sn/Al2O3 catalyst also showed high activity in NO3− reduction from drinking waters of weak mineralization, with a slightly increase of the selectivity towards NH4+ with respect to the obtained in deionized water with NO3− as the only anionThe authors wish to thank for the financial support the Spanish MINECO ( PID2019-108445RB-I00 ) and Comunidad de Madrid ( BIOTRES-CM , S2018/EMT-4344 ). I. Sanchis also thanks Comunidad de Madrid for award of a research grant ( PEJD-265 2017-PRE/AMB-4616