University of Freiburg

About: University of Freiburg is a education organization based out in Freiburg, Baden-Württemberg, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 41992 authors who have published 77296 publications receiving 2896269 citations. The organization is also known as: alberto-ludoviciana & Albert-Ludwigs-Universität Freiburg.

Tracking multiple moving targets with a mobile robot using particle filters and statistical data association

Abstract: One of the goals in the field of mobile robotics is the development of mobile platforms which operate in populated environments and offer various services to humans. For many tasks it is highly desirable that a robot can determine the positions of the humans in its surrounding. In this paper we present a method for tracking multiple moving objects with a mobile robot. We introduce a sample-based variant of joint probabilistic data association filters to track features originating from individual objects and to solve the correspondence problem between the detected features and the filters. In contrast to standard methods, occlusions are handled explicitly during data association. The technique has been implemented and tested on a real robot. Experiments carried out in a typical office environment show that the method is able to track multiple persons even when the trajectories of two people are crossing each other.

Control of Confounding and Reporting of Results in Causal Inference Studies. Guidance for Authors from Editors of Respiratory, Sleep, and Critical Care Journals

Abstract: Control of Confounding and Reporting of Results in Causal Inference Studies Guidance for Authors fromEditors of Respiratory, Sleep, andCritical Care Journals David J. Lederer*, Scott C. Bell*, Richard D. Branson*, James D. Chalmers*, Rachel Marshall*, David M. Maslove*, David E. Ost*, Naresh M. Punjabi*, Michael Schatz*, Alan R. Smyth*, Paul W. Stewart*, Samy Suissa*, Alex A. Adjei, Cezmi A. Akdis, Élie Azoulay, Jan Bakker, Zuhair K. Ballas, Philip G. Bardin, Esther Barreiro, Rinaldo Bellomo, Jonathan A. Bernstein, Vito Brusasco, Timothy G. Buchman, Sudhansu Chokroverty, Nancy A. Collop, James D. Crapo, Dominic A. Fitzgerald, Lauren Hale, Nicholas Hart, Felix J. Herth, Theodore J. Iwashyna, Gisli Jenkins, Martin Kolb, Guy B. Marks, Peter Mazzone, J. Randall Moorman, ThomasM.Murphy, Terry L. Noah, Paul Reynolds, Dieter Riemann, Richard E. Russell, Aziz Sheikh, Giovanni Sotgiu, Erik R. Swenson, Rhonda Szczesniak, Ronald Szymusiak, Jean-Louis Teboul, and Jean-Louis Vincent Department of Medicine and Department of Epidemiology, Columbia University Irving Medical Center, New York, New York; Editor-inChief, Annals of the American Thoracic Society; Department of Thoracic Medicine, The Prince Charles Hospital, Brisbane, Queensland, Australia; Editor-in-Chief, Journal of Cystic Fibrosis; Department of Surgery, University of Cincinnati, Cincinnati, Ohio; Editor-in-Chief, Respiratory Care; University of Dundee, Dundee, Scotland; Deputy Chief Editor, European Respiratory Journal; London, England; Deputy Editor, The Lancet Respiratory Medicine; Department of Medicine, Queen’s University, Kingston, Ontario, Canada; Associate Editor for Data Science, Critical Care Medicine; Department of Pulmonary Medicine, University of Texas MD Anderson Cancer Center, Houston, Texas; Editor-in-Chief, Journal of Bronchology and Interventional Pulmonology; Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland; Deputy Editor-in-Chief, SLEEP; Department of Allergy, Kaiser Permanente Medical Center, San Diego, California; Editor-in-Chief, The Journal of Allergy & Clinical Immunology: In Practice; Division of Child Health, Obstetrics, and Gynecology, University of Nottingham, Nottingham, England; Joint Editor-in-Chief, Thorax; Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina; Associate Editor, Pediatric Pulmonology; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada; Advisor, COPD: Journal of Chronic Obstructive Pulmonary Disease; Department of Oncology, Mayo Clinic, Rochester, Minnesota; Editor-in-Chief, Journal of Thoracic Oncology; Swiss Institute of Allergy and Asthma Research, University of Zurich, Davos, Switzerland; Editor-in-Chief, Allergy; St. Louis Hospital, University of Paris, Paris, France; Editor-in-Chief, Intensive Care Medicine; Department of Medicine, Columbia University Irving Medical Center, and Division of Pulmonary, Critical Care, and Sleep, NYU Langone Health, New York, New York; Department of Intensive Care Adults, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Intensive Care, Pontificia Universidad Católica de Chile, Santiago, Chile; Editor-in-Chief, Journal of Critical Care; Department of Internal Medicine, University of Iowa and the Iowa City Veterans Affairs Medical Center, Iowa City, Iowa; Editor-in-Chief, The Journal of Allergy and Clinical Immunology; Monash Lung and Sleep, Monash Hospital and University, Melbourne, Victoria, Australia; Co-Editor-in-Chief, Respirology; Pulmonology Department, Muscle and Lung Cancer Research Group, Research Institute of Hospital del Mar and Centro de Investigación Biomédica en Red Enfermedades Respiratorias Instituto de Salud Carlos III, Barcelona, Spain; Editor-in-Chief, Archivos de Bronconeumologia; Department of Intensive Care Medicine, Austin Hospital and University of Melbourne, Melbourne, Victoria, Australia; Editor-in-Chief, Critical Care & Resuscitation; Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, Ohio; Editor-in-Chief, Journal of Asthma; Department of Internal Medicine, University of Genoa, Genoa, Italy; Editor-in-Chief, COPD: Journal of Chronic Obstructive Pulmonary Disease; Department of Surgery, Department of Anesthesiology, and Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia; Editor-in-Chief,Critical CareMedicine; JFKNewJersey Neuroscience Institute, HackensackMeridian Health–JFKMedical Center, Edison, New Jersey; Editor-in-Chief, Sleep Medicine; Department of Medicine and Department of Neurology, Emory University School of Medicine, Atlanta, Georgia; Editor-in-Chief, Journal of Clinical Sleep Medicine; Department of Medicine, National Jewish Hospital, Denver, Colorado; Editor-in-Chief, Journal of the COPD Foundation; The Children’s Hospital at Westmead, Sydney Medical School, University of

Resolving the clinical acuity categories "hand motion" and "counting fingers" using the Freiburg Visual Acuity Test (FrACT).

Abstract: The Freiburg Visual Acuity Test (FrACT) has been suggested as a promising test for quantifying the visual acuity (VA) of patients with very low vision, a condition often classified using the semi-quantitative clinical scale “counting fingers” (CF), “hand motion” (HM), “light perception” (LP) and “no light perception”. The present study was designed to assess FrACT performance in a sizable number of CF, HM, and LP patients in order to generate a setting for future clinical studies in the low vision range. We examined a total of 41 patients (LP, n = 11; CF, n = 15; HM, n = 15) with various eye diseases (e.g., diabetic retinopathy, ARMD), covering the clinical VA scale from LP to CF. The FrACT optotypes were presented at a distance of 50 cm on a 17-inch LCD monitor with four random orientations. After training, two FrACT measurements (test and retest) were taken, each comprising 30 trials. FrACT measures reproducibly the VA of CF and HM patients. In CF patients, FrACT resulted in a mean logMAR = 1.98 ± 0.24 (corresponding to a decimal VA of 0.010), for HM in a mean logMAR = 2.28 ± 0.15 (corresponding to a decimal VA of 0.0052). In all LP patients the FrACT values were close to what would be obtained by random guessing. The mean test–retest 95% confidence interval was 0.21 logMAR for CF patients and 0.31 logMAR for HM respectively. Test-retest variability declined from 24 to 30 trials, showing that at least 30 trials are necessary. FrACT can reproducibly quantify VA in the CF and HM range. We observed a floor effect for LP, and it was not quantifiable further. Quantitative VA measures are thus obtainable in the very low-vision range using FrACT.

Learning Motion Patterns of People for Compliant Robot Motion

Abstract: Whenever people move through their environments they do not move randomly. Instead, they usually follow specific trajectories or motion patterns corresponding to their intentions. Knowledge about such patterns enables a mobile robot to robustly keep track of persons in its environment and to improve its behavior. In this paper we propose a technique for learning collections of trajectories that characterize typical motion patterns of persons. Data recorded with laser-range finders are clustered using the expectation maximization algorithm. Based on the result of the clustering process, we derive a hidden Markov model that is applied to estimate the current and future positions of persons based on sensory input. We also describe how to incorporate the probabilistic belief about the potential trajectories of persons into the path planning process of a mobile robot. We present several experiments carried out in different environments with a mobile robot equipped with a laser-range scanner and a camera system. The results demonstrate that our approach can reliably learn motion patterns of persons, can robustly estimate and predict positions of persons, and can be used to improve the navigation behavior of a mobile robot.

Multi-view 3D Models from Single Images with a Convolutional Network

Abstract: We present a convolutional network capable of inferring a 3D representation of a previously unseen object given a single image of this object. Concretely, the network can predict an RGB image and a depth map of the object as seen from an arbitrary view. Several of these depth maps fused together give a full point cloud of the object. The point cloud can in turn be transformed into a surface mesh. The network is trained on renderings of synthetic 3D models of cars and chairs. It successfully deals with objects on cluttered background and generates reasonable predictions for real images of cars.