You are here! Finding position and orientation on a 2D map from a single image: The Flatlandia localization problem and dataset

We introduce Flatlandia, a novel problem for visual localization of an image from object detections composed of two specific tasks: i) Coarse Map Localization: localizing a single image observing a set of objects in respect to a 2D map of object landmarks; ii) Fine-grained 3DoF Localization: estimating latitude, longitude, and orientation of the image within a 2D map. Solutions for these new tasks exploit the wide availability of open urban maps annotated with GPS locations of common objects (\eg via surveying or crowd-sourced). Such maps are also more storage-friendly than standard large-scale 3D models often used in visual localization while additionally being privacy-preserving. As existing datasets are unsuited for the proposed problem, we provide the Flatlandia dataset, designed for 3DoF visual localization in multiple urban settings and based on crowd-sourced data from five European cities. We use the Flatlandia dataset to validate the complexity of the proposed tasks

Obesity as a risk factor for unfavourable outcomes in critically ill patients affected by Covid 19

BACKGROUND AND AIMS: Recent studies show that obesity is a risk factor for hospital admission and for critical care need in patients with coronavirus disease 2019 (COVID-19). The aim was to determine whether obesity is a risk factor for unfavourable health outcomes in patients affected by COVID-19 admitted to ICU.METHODS AND RESULTS: 95 consecutive patients with COVID-19 (78 males and 18 females) were admitted to ICU and included in the study. Height, weight, BMI, Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, CRP, CPK, ICU and hospital length of stay and comorbidities were evaluated. Participants with obesity had a lower 28 day survival rate from ICU admission than normal weight subjects. Cox proportional hazard model-derived estimates, adjusted for age, gender and comorbidity, confirmed the results of the survival analysis (HR:5.30,95%C.I.1.26-22.34). Obese subjects showed longer hospital and ICU stay as compared with normal weight counterpart.Subjects with obesity showed significantly higher CRP and CPK levels than normal weight subjects.CONCLUSION: In individuals with obesity, careful management and prompt intervention in case of suspected SARS-CoV-2 infection is necessary to prevent the progression of the disease towards severe outcomes and the increase of hospital treatment costs

Solidification microstructure of centrifugally cast Inconel 625

Centrifugal casting is a foundry process allowing the production of near net-shaped axially symmetrical components. The present study focuses on the microstructural characterization of centrifugally cast alloys featuring different chemical compositions for the construction of spheres applied in valves made of alloy IN625 for operation at high pressure. Control of the solidification microstructure is needed to assure the reliability of the castings. Actually, a Ni-base superalloy such as this one should have an outstanding combination of mechanical properties, high temperature stability and corrosion resistance. Alloys such as IN625 are characterised by a large amount of alloying elements and a wide solidification range, so they can be affected by micro-porosity defects, related to the shrinkage difference between the matrix and the secondary reinforcing phases (Nb-rich carbides and Laves phase). In this study, the microstructure characterization was performed as a function of the applied heat treatments and it was coupled with a calorimetric analysis in order to understand the mechanism ruling the formation of micro-porosities that can assure alloy soundness. The obtained results show that the presence of micro-porosities is governed by morphology and by the size of the secondary phases, and the presence of the observed secondary phases is detrimental to corrosion resistance

Uncontrolled donation after circulatory death and liver transplantation: much still remains to be done

uncontrolled donation after circulatory death represents a challenging strategy to increase the donor pool. In this article the technical and ethical issues are discusse

3d tracking by catadioptric vision based on particle filters

Abstract. This paper presents a robust tracking system for autonomous robots equipped with omnidirectional cameras. The proposed method uses a 3D shape and color-based object model. This allows to tackle difficulties that arise when the tracked object is placed above the ground plane floor. Tracking under these conditions has two major difficulties: first, observation with omnidirectional sensors largely deforms the target’s shape; second, the object of interest embedded in a dynamic scenario may suffer from occlusion, overlap and ambiguities. To surmount these difficulties, we use a 3D particle filter to represent the target’s state space: position and velocity with respect to the robot. To compute the likelihood of each particle the following features are taken into account: i) image color; ii) mismatch between target’s color and background color. We test the accuracy of the algorithm in a RoboCup Middle Size League scenario, both with static and moving targets.

SVP-Classifier: Single-View Point Cloud Data Classifier with Multi-view Hallucination

We address single-view 3D shape classification with partial Point Cloud Data (PCD) inputs. Conventional PCD classifiers achieve the best performance when trained and evaluated with complete 3D object scans. However, they all experience a performance drop when trained and evaluated on partial single-view PCD. We propose a Single-View PCD Classifier (SVP-Classifier), which first hallucinates the features of other viewpoints covering the unseen part of the object with a Conditional Variational Auto-Encoder (CVAE). It then aggregates the hallucinated multi-view features with a multi-level Graph Convolutional Network (GCN) to form a global shape representation that helps to improve the single-view PCD classification performance. With experiments on the single-view PCDs generated from ModelNet40 and ScanObjectNN, we prove that the proposed SVP-Classifier outperforms the best single-view PCD-based methods, after they have been retrained on single-view PCDs, thus reducing the gap between single-view methods and methods that employ complete PCDs. Code and datasets are available: https://github.com/IIT-PAVIS/SVP-Classifier

3DSGrasp: 3D Shape-Completion for Robotic Grasp

Real-world robotic grasping can be done robustly if a complete 3D Point Cloud Data (PCD) of an object is available. However, in practice, PCDs are often incomplete when objects are viewed from few and sparse viewpoints before the grasping action, leading to the generation of wrong or inaccurate grasp poses. We propose a novel grasping strategy, named 3DSGrasp, that predicts the missing geometry from the partial PCD to produce reliable grasp poses. Our proposed PCD completion network is a Transformer-based encoder-decoder network with an Offset-Attention layer. Our network is inherently invariant to the object pose and point's permutation, which generates PCDs that are geometrically consistent and completed properly. Experiments on a wide range of partial PCD show that 3DSGrasp outperforms the best state-of-the-art method on PCD completion tasks and largely improves the grasping success rate in real-world scenarios. The code and dataset are available at: https://github.com/NunoDuarte/3DSGrasp

Analysis of P(v-a)CO2/C(a-v)O2 Ratio and Other Perfusion Markers in a Population of 98 Pediatric Patients Undergoing Cardiac Surgery

Background: The so-called Low Cardiac Output Syndrome (LCOS) is one of the most common complications in pediatric patients with congenital heart disease undergoing corrective surgery. LCOS requires high concentrations of inotropes to support cardiac contractility and improve cardiac output, allowing for better systemic perfusion. To date, serum lactate concentrations and central venous oxygen saturation (ScVO2) are the most commonly used perfusion markers, but they are not completely reliable in identifying a state of global tissue hypoxia. The study aims to evaluate whether the venoarterial carbon dioxide difference/arterial-venous oxygen difference ratio [P(v-a)CO2/C(a-v)O-2] can be a good index to predict the development of LCOS in the aforementioned patients, so as to treat it promptly. Methods: This study followed a population of 98 children undergoing corrective cardiac surgery from June 2018 to October 2020 at the Department of Cardiac Surgery of University Hospital Integrated Trust and their subsequent admission at the Postoperative Cardiothoracic Surgery Intensive Care Unit. During the study, central arterial and venous blood gas analyses were carried out before and after cardiopulmonary bypass (CPB) (pre-CPB and post-CPB), at admission to the intensive care unit, before and after extubation, and at any time of instability or modification of the patient's clinical and therapeutic conditions. Results: The data analysis shows that 46.9% of the children developed LCOS (in line with the current literature) but that there is no statistically significant association between the P(v-a)CO2/C(a-v)O-2 ratio and LCOS onset. Despite the limits of statistical significance, however, a 31% increase in the ratio emerged from the pre-CPB phase to the post-CPB phase when LCOS is present. Conclusions: This study confirms a statistically significant association between the most used markers in adult patients (serum lactate concentration, ScVO2, and oxygen extraction ratio-ERO2) measured in the pre-CPB phase and the incidence of LCOS onset, especially in patients with hemodynamic instability before surgery