Automobile indexation from 3D point clouds of urban scenarios

In this paper, we introduce a methodology for the detection and segmentation of automobiles in urban scenarios. We use the LiDAR Velodyne HDL-64E to scan the surroundings. The method is comprised of three steps: (1) remove facades, ground plan, and unstructured objects, (2) smoothing data using robust principal component analysis (RPCA), and finally, (3) unstructured objects model and indexing. The dataset is partitioned into training with 4500 objects and test with 3000 objects. Mean Shift thresholds, the filter, the Delaunay parameters, and the histogram modelling are optimized via ROC analysis. It is observed that the car scan quality affects our method to a lesser degree when compared with state-of-the-art methods

Hand features extractor using hand contour – a case study

Hand gesture recognition is an important topic in natural user interfaces (NUI). Hand features extraction is the first step for hand gesture recognition. This work proposes a novel real time method for hand features recognition. In our framework we use three cameras and the hand region is extracted with the background subtraction method. Features like arm angle and fingers positions are calculated using Y variations in the vertical contour image. Wrist detection is obtained by calculating the bigger distance from a base line and the hand contour, giving the main features for the hand gesture recognition. Experiments on our own data-set of about 1800 images show that our method performs well and is highly efficient

Análisis del desempeño cinetostático de un robot paralelo tipo Delta reconfigurable

ResumenEn este trabajo se presenta el análisis del desempeño cinetostático de un robot paralelo tipo Delta cuando se somete a una estrategia de reconfiguración geométrica. Se evalúan tres alternativas de reconfiguración, seleccionando la que se logra por el ajuste simétrico del tamaño de la base fija del robot. El análisis del efecto de la reconfiguración geométrica sobre el desempeño cinetostático del robot se realiza a través del número de condición de la matriz jacobiana, por lo que fue necesario desarrollar previamente el modelo cinemático del manipulador en posición y velocidad. Ambas aproximaciones son diferentes a las comúnmente encontradas en la literatura; destacándose el análisis de velocidad, el cual se realiza con teoría de tornillos. Los resultados de este trabajo apuntan a que con una estrategia de reconfiguración geométrica se puede mejorar el desempeño cinetostático del robot tipo Delta en todo su espacio de trabajo operable, además sugieren la conveniencia de la utilización del número de condición de la matriz Jacobiana como criterio para determinar la configuración geométrica óptima del manipulador dentro de ciertos parámetros.AbstractThis paper presents the kinetostatic performance analysis of a reconfigurable Deltatype parallel robot when a geometrical reconfiguration strategy is done. Three reconfiguration alternatives were evaluated, and the chosen strategy was based on the symmetrical size adjustment of the robot's fixed base. The analysis of the geometrical reconfiguration's effect on the robot's kinetostatic performance is obtained with the condition number of the Jacobian matrix, for which it was previously needed to develop the position and velocity kinematic model of the manipulator. Both approaches are different from those commonly found in the literature; with the velocity analysis standing out by the use of screw theory. The results of this work suggest a geometric strategy of reconfiguration for the improvement of the kinetostatic performance of the Delta robot in the entirety of its operable workspace. In addition, this work shows the convenience of the use of the condition number of the Jacobian matrix as criteria for determining the optimal geometric configuration of the manipulator inside certain parameters

Digitalización del entorno a partir de un LIDAR HDL-64E

This paper proposes a map building system for an autonomous vehicle equipped with LIDAR technology, capable to obtain more than one million points per second. This paper proposes a Fast Local Map building Approach (LM) that it is use for autonomous local navigation, and construction of Global Map (GM) 2D and 3D for modeling the whole environment crossed by the vehicle. During the process of the global map building, we estimate the location of the vehicle with respect to its initial position.DOI: http://dx.doi.org/10.5377/nexo.v25i1.795 Nexo Revista Científica,Vol. 25, No. 01, pp.28-37/Junio 2012 En este trabajo se propone un sistema de reconstrucción de mapas para un vehículo autónomo equipado con tecnología LIDAR, capaz de obtener más de un millón de puntos por segundo. Dentro del artículo proponemos la construcción rápida de Mapas Locales (ML) 2D que nos servirán para la navegación local autónoma, y la construcción de Mapas Globales (MG) 2D y 3D que modelizán el ambiente recorrido por el vehículo. Durante el proceso de construcción del Mapa Global se calcula la localización del vehículo con respecto a su posición inicial.DOI: http://dx.doi.org/10.5377/nexo.v25i1.795 Nexo Revista Científica,Vol. 25, No. 01, pp.28-37/Junio 2012

Digitalización del entorno a partir de un LIDAR HDL-64E

This paper proposes a map building system for an autonomous vehicle equipped with LIDAR technology, capable to obtain more than one million points per second. This paper proposes a Fast Local Map building Approach (LM) that it is use for autonomous local navigation, and construction of Global Map (GM) 2D and 3D for modeling the whole environment crossed by the vehicle. During the process of the global map building, we estimate the location of the vehicle with respect to its initial position.Keywords: 2D map building, 3D map building, localization.En este trabajo se propone un sistema de reconstrucción de mapas para un vehículo autónomo equipado con tecnología LIDAR, capaz de obtener más de un millón de puntos por segundo. Dentro del artículo proponemos la construcción rápida de Mapas Locales (ML) 2D que nos servirán para la navegación local autónoma, y la construcción de Mapas Globales (MG) 2D y 3D que modelizán el ambiente recorrido por el vehículo. Durante el proceso de construcción del Mapa Global se calcula la localización del vehículo con respecto a su posición inicial.Palabras claves: Construcción de mapas 2D, construcción de mapas 3D, localización

Performance evaluation of a portable 3D vision coordinate measuring system

In this work, we present a portable 3D vision coordinate measuring machine (PCMM) for short range-real time photogrammetry. The PCMM performs 3D measurements of points using a single camera in combination with a hand tool and a computer. The hand tool has infrared LEDs serving as photogrammetric targets. The positions of these targets were pre-calibrated with an optical coordinate-measuring machine defining a local coordinate system on the hand tool. The camera has an infrared filter to exclude all ambient light but infrared targets. Positions of the imaged infrared targets are converted to 3D coordinates using pixel positions and precalibrated positions of the targets. Also, we present a set of criteria for selecting the infrared LEDs and the camera filter, a camera calibration method, a tracking and POSE algorithms, and a 3D coordinate error correction for the PCMM. The correction is performed using the PCMM as a range meter, which implies comparing the 3D coordinate points of the PCMM with a coordinate measuring machine, and then generating a look up table (LUT) for correction. The global error of the PCMM was evaluated under ASME B89.4.22-2004. Sphere and single point errors were around 1 mm, volumetric error were under 3 mm

Sistema de visión sinérgico para detección de movimiento

La detección de movimiento en sistemas de vigilancia y monitoreo se ve favorecida por la combinación sinérgica de diferentes tipos de cámaras y su óptima distribución sobre el área de interés. Se propone un modelo de optimización para un sistema de visión sinérgico basado en programación lineal entera. Los objetivos son encontrar la posición y orientación óptima de cada una de las cámaras direccionales y omnidireccionales con el fin de maximizar la cobertura del espacio de trabajo y detectar los objetos en movimiento presentes. Para detectar eficientemente el movimiento, incluso ante cambios de luminosidad globales, se utiliza un algoritmo de substracción de fondo que usa la información espacial de la textura. El método propuesto se evalúa en un conjunto representativo de escenarios reales utilizando una red de cámaras. Los resultados muestran que nuestro algoritmo es capaz de determinar el número mínimo de cámaras necesario para cubrir un área determinada

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Dynamic Measurement of Portos Tomato Seedling Growth Using the Kinect 2.0 Sensor

Traditionally farmers monitor their crops employing their senses and experience. However, the human sensory system is inconsistent due to stress, health, and age. In this paper, we propose an agronomic application for monitoring the growth of Portos tomato seedlings using Kinect 2.0 to build a more accurate, cost-effective, and portable system. The proposed methodology classifies the tomato seedlings into four categories: The first corresponds to the seedling with normal growth at the time of germination; the second corresponds to germination that occurred days after; the third category entails exceedingly late germination where its growth will be outside of the estimated harvest time; the fourth category corresponds to seedlings that did not germinate. Typically, an expert performs this classification by analyzing ten percent of the randomly selected seedlings. In this work, we studied different methods of segmentation and classification where the Gaussian Mixture Model (GMM) and Decision Tree Classifier (DTC) showed the best performance in segmenting and classifying Portos tomato seedlings