Differential epipolar constraint in mobile robot egomotion estimation

The estimation of camera egomotion is a well established problem in computer vision. Many approaches have been proposed based on both the discrete and the differential epipolar constraint. The discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with a unique moving camera. The article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. Results from real data are also given

Surface registration from range image fusion

The registration of full 3-D models is an important task in computer vision. Range finders only reconstruct a partial view of the object. Many authors have proposed several techniques to register 3D surfaces from multiple views in which there are basically two aspects to consider. First, poor registration in which some sort of correspondences are established. Second, accurate registration in order to obtain a better solution. A survey of the most common techniques is presented and includes experimental results of some of them

Accuracy estimation of a new omnidirectional 3D vision sensor

We present a computer vision system that associates omnidirectional vision with structured light with the aim of obtaining depth information for a 360 degrees field of view. The approach proposed in this article combines an omnidirectional camera with a panoramic laser projector. The article shows how the sensor is modelled and its accuracy is proved by means of experimental results. The proposed sensor provides useful information for robot navigation applications, pipe inspection, 3D scene modelling etc

A survey addressing the fundamental matrix estimation problem

Epipolar geometry is a key point in computer vision and the fundamental matrix estimation is the only way to compute it. This article surveys several methods of fundamental matrix estimation which have been classified into linear methods, iterative methods and robust methods. All of these methods have been programmed and their accuracy analysed using real images. A summary, accompanied with experimental results, is given

Estimation of the probability of congestion using Monte Carlo method in OPS networks

In networks with small buffers, such as optical packet switching based networks, the convolution approach is presented as one of the most accurate method used for the connection admission control. Admission control and resource management have been addressed in other works oriented to bursty traffic and ATM. This paper focuses on heterogeneous traffic in OPS based networks. Using heterogeneous traffic and bufferless networks the enhanced convolution approach is a good solution. However, both methods (CA and ECA) present a high computational cost for high number of connections. Two new mechanisms (UMCA and ISCA) based on Monte Carlo method are proposed to overcome this drawback. Simulation results show that our proposals achieve lower computational cost compared to enhanced convolution approach with an small stochastic error in the probability estimation

Standardisation of the waist circumference (WC) for each range of body mass index (BMI) in adult outpatients attended to in Endocrinology and Nutrition departments

By this study we seek the expectable range of waist circumference (WC) for every degree of body mass index (BMI), which will serve to studies targeting ascertaining the health risk. We studied 2,932 patients (39.6% men and 60.4% women, between 18 and 96 years ) of the same ethnic group who consecutively attended outpatient departments of our clinics between 2000 and 2004. BMI correlated linearly with the WC (cc: 0.85; p < 0.001). The men, the obese, and diabetics were older (p < 0.001). BMI was greater in women and WC in men. The women had a greater WC if they had diabetes (p < 0.01), being equal to diabetic males. The men had greater WC when they had diabetes (p < 0.001). Waist at risk was detected (men > or = 102 cm and women > or = 88 cm) in 94.3% of the obese, in 32.3% of overweight patients, in 3.8% of patients with BMI < 25, in 84.3% of diabetics, and in 72.6% of patients without diabetes. We made graphic standardisation of WC with regard to BMI, and we calculated the percentiles 10, 25, 50, 75 and 90, grouping in ranges of 2 kg/m(2) of BMI. The diabetic patients are grouped in ranges of 4 kg/m(2). As conclusion we present a standardisation of the WC measurement of patients attended to in our Endocrinology and Nutrition practices distributed in percentiles as a clinically usable tool to define the ranges of WC for every BMI value.

Estimation of the lateral correlation structure of subsurface water content from surface-based ground-penetrating radar reflection images

Over the past decade, significant interest has been expressed in relating the spatial statistics of surface-based reflection ground-penetrating radar (GPR) data to those of the imaged subsurface volume. A primary motivation for this work is that changes in the radar wave velocity, which largely control the character of the observed data, are expected to be related to corresponding changes in subsurface water content. Although previous work has indeed indicated that the spatial statistics of GPR images are linked to those of the water content distribution of the probed region, a viable method for quantitatively analyzing the GPR data and solving the corresponding inverse problem has not yet been presented. Here we address this issue by first deriving a relationship between the 2-D autocorrelation of a water content distribution and that of the corresponding GPR reflection image. We then show how a Bayesian inversion strategy based on Markov chain Monte Carlo sampling can be used to estimate the posterior distribution of subsurface correlation model parameters that are consistent with the GPR data. Our results indicate that if the underlying assumptions are valid and we possess adequate prior knowledge regarding the water content distribution, in particular its vertical variability, this methodology allows not only for the reliable recovery of lateral correlation model parameters but also for estimates of parameter uncertainties. In the case where prior knowledge regarding the vertical variability of water content is not available, the results show that the methodology still reliably recovers the aspect ratio of the heterogeneity.

Intelligent PCA contribution analysis for quality estimation in batch processes. Application in a sequencing batch reactor for wastewater treatment

En aquest treball, es proposa un nou mètode per estimar en temps real la qualitat del producte final en processos per lot. Aquest mètode permet reduir el temps necessari per obtenir els resultats de qualitat de les anàlisi de laboratori. S'utiliza un model de anàlisi de componentes principals (PCA) construït amb dades històriques en condicions normals de funcionament per discernir si un lot finalizat és normal o no. Es calcula una signatura de falla pels lots anormals i es passa a través d'un model de classificació per la seva estimació. L'estudi proposa un mètode per utilitzar la informació de les gràfiques de contribució basat en les signatures de falla, on els indicadors representen el comportament de les variables al llarg del procés en les diferentes etapes. Un conjunt de dades compost per la signatura de falla dels lots anormals històrics es construeix per cercar els patrons i entrenar els models de classifcació per estimar els resultas dels lots futurs. La metodologia proposada s'ha aplicat a un reactor seqüencial per lots (SBR). Diversos algoritmes de classificació es proven per demostrar les possibilitats de la metodologia proposada.

Sandflies (Diptera: Psychodidae) from caves of the quartzite Espinhaço Range, Minas Gerais, Brazil

This study investigated the sandfly fauna of two quartzite caves in the Espinhaço Mountain Range, located in the municipality of Diamantina, state Minas Gerais. From August 2010-July 2011, entomological sampling was performed in the caves of Salitre and Monte Cristo with two HP light traps exposed in the photic and aphotic zones of each cave. The sandfly fauna consisted of 17 species, among which Lutzomyia cipoensis was predominant (54.76%). The male/female ratio in the total captures was 1:2.5. The aphotic zone showed the highest frequency of specimens captured (65%). A greater density of sandflies occurred during the summer (January-February), coinciding with the period of higher temperatures, humidity and rainfall. The presence of Lutzomyia longipalpis, Lutzomyia whitmani and Lutzomyia pessoai, proven or suspected vectors of leishmaniasis, is of concern because the area is visited by many tourists.

Performance de l'estimation du poids foetal par echographie pour les foetus < or = 2000 g et les macrosomes (> or = 4000 g) [Performance of ultrasound estimation of fetal weight in fetuses weighing < or = 2000 g and more than 4000 g].

Decreasing perinatal morbidity and mortality is one of the main goals of obstetrics. Prognosis of preterm births depends on gestational age and birthweight. Multidisciplinary management is discussed with the parents according to these two parameters. In other circumstances, a suspected macrosomy will influence the management of the last weeks of pregnancy. Induction of labor or Cesarean delivery will be considered to avoid shoulder dystocia, brachial plexus injury or perinatal asphyxia. Birthweight needs to be estimated with accuracy, and this article describes the efficiency of various ultrasound weight estimation formulae for small and large fetuses.

A Bayesian approach for pervasive estimation of breaststroke velocity using a wearable IMU

A ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every cycle using a low-cost wearable inertial measurement unit (IMU). The statistical validation of the method on 15 swimmers shows that an average relative error of 0.1 ± 9.6% and high correlation with the tethered reference system (rX,Y=0.91 ) is achievable. Besides, a simple tool to analyze the influence of sacrum kinematics on the performance is provided.

Nonparametric estimation of Value-at-Risk

A method to estimate an extreme quantile that requires no distributional assumptions is presented. The approach is based on transformed kernel estimation of the cumulative distribution function (cdf). The proposed method consists of a double transformation kernel estimation. We derive optimal bandwidth selection methods that have a direct expression for the smoothing parameter. The bandwidth can accommodate to the given quantile level. The procedure is useful for large data sets and improves quantile estimation compared to other methods in heavy tailed distributions. Implementation is straightforward and R programs are available.