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IEEE International Instrumentation and Measurement Technology Conference

作者： Sami Varjo Ville Kaikkonen Jari Hannuksela Anssi Makynen The Center for Machine Vision Research Department of Computer Science and Engineering University of Oulu Oulu Finland Unit for Measurement Technology CEMIS-Oulu University of Oulu Kajaani Finland Optoelectronics and Measurement Techniques Laboratory University of Oulu Oulu Finland

ISBN: (纸本)9781479961153

In-line holography enables particle measurements in large imaging volumes with an extended depth of field compared with conventional imaging systems. Accurate measurements of the structural details of the particles are practically possible only if the measured details are brought in focus. In order to extract in-focus images of objects recorded into a digital hologram from a large set of holograms in a feasible manner, automated focusing and segmentation are needed. The twin image present inheritently in the in-line holography data leads to extra noise that makes this a challenging problem. We propose a new depth estimation method for in-line holography, where the stack of reconstructed intensity images is analyzed. First rough object locations are estimated where the object depths are estimated with a wavelet based focus measure. Clusters of depth estimates are used with plane fitting to approximate the object orientation in the 3D volume to obtain the final all-in-focus images. We show that the proposed method can be used to obtain sharp images of planar objects, such as snowflakes.

关键词： Image reconstruction Holography Particle measurements Frequency measurement Atmospheric measurements Noise

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User customizable interaction in coexistence space

User customizable interaction in coexistence space

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： KangGeon Kim Myoung Soo Park Jung-Min Park Computer Science Department University of Southern California USA Interaction and Robotics Research Center Korea Institute of Science and Technology Seoul Korea

ISBN: (纸本)9781479953349

This paper proposes a user customizable interface for user-centered interaction in a space where the real, virtual and remote world is unified and indistinguishable through a combination of humans, artifacts and a virtual world. We have developed a new user customizable interface, which is a set according to the preferences of users and is intuitive and natural to minimize inconvenience of using the dedicated interface. We have executed several experiments using user gestural expression as user customizable interface such as: various devices control, object handling, environmental interaction, and command transmission in the space. The results of the demonstration have shown that effective interaction with a user customizable interface is possible among the real, virtual and remote worlds.

关键词： User interfaces Aerospace electronics Robot sensing systems Gesture recognition Real-time systems Electronic mail

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Extended local binary pattern fusion for face recognition

Extended local binary pattern fusion for face recognition

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作者： Liu, Li Fieguth, Paul Zhao, Guoying Pietikainen, Matti School of Information System and Management National University of Defense Technology Changsha410073 China Department of Systems Design Engineering University of Waterloo WaterlooN2L 3G1 Canada Center for Machine Vision Research Department of Computer Science and Engineering University of Oulu Oulu90014 Finland

ISBN: (纸本)9781479957514

This paper presents a simple, novel, yet highly effective approach for robust face recognition. Given LBP-like descriptors based on local accumulated pixel differences, Angular Differences (AD) and Radial Differences (RD), the local differences are decomposed into complementary components of signs and magnitudes. The proposed descriptors have desirable features: (1) robustness to lighting, pose, and expression;(2) computation efficiency;(3) encoding of both microstructures and macrostructures;(4) consistent in form with traditional LBP, thus inheriting the merits of LBP;and (5) no required training, improving generalizability. From a given face image, we obtain six histogram features, each of which is obtained by concatenating spatial histograms extracted from nonoverlapping subregions. The Whitened PCA technique is used for dimensionality reduction, followed by Nearest Neighbor classification. We have evaluated the effectiveness of the proposed method on the Extended Yale B and CAS-PEAL-R1 databases. The proposed method impressively outperforms other well known systems, including what we believe to be the best reported performance for the the CAS-PEAL-R1 lighting probe set with a recognition rate of 72.3%. © 2014 IEEE.

关键词： Local binary pattern

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Erratum to: Methods for evaluating medical tests and biomarkers

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Diagnostic and prognostic research 2017年第1期1卷 11页

作者： Gowri Gopalakrishna Miranda Langendam Rob Scholten Patrick Bossuyt Mariska Leeflang Anna Noel-Storr James Thomas Iain Marshall Byron Wallace Penny Whiting Clare Davenport Gowri GopalaKrishna Isabel de Salis Sue Mallett Robert Wolff Richard Riley Marie Westwood Jos Kleinen Gary Collins Hans Reitsma Karel Moons Antonia Zapf Annika Hoyer Katharina Kramer Oliver Kuss J Ensor J J Deeks E C Martin R D Riley Gerta Rücker Susanne Steinhauser Martin Schumacher Joie Ensor Kym Snell Brian Willis Thomas Debray Jon Deeks Lavinia Ferrante di Ruffano Sian Taylor-Phillips Chris Hyde Stuart A Taylor Gauraang Batnagar Lavinia Ferrante Di Ruffano Farah Seedat Aileen Clarke Sarah Byron Frances Nixon Rebecca Albrow Thomas Walker Carla Deakin Zhivko Zhelev Harriet Hunt Yaling Yang Lucy Abel James Buchanan Thomas Fanshawe Bethany Shinkins Laure Wynants Jan Verbakel Sabine Van Huffel Dirk Timmerman Ben Van Calster Aeliko Zwinderman Jason Oke Jack O'Sullivan Rafael Perera Brian Nicholson Hannah L Bromley Tracy E Roberts Adele Francis Denniis Petrie G Bruce Mann Kinga Malottki Holly Smith Lucinda Billingham Alice Sitch Oke Gerke Mie Holm-Vilstrup Eivind Antonsen Segtnan Ulrich Halekoh Poul Flemming Høilund-Carlsen Bernard G Francq Jac Dinnes Julie Parkes Walter Gregory Jenny Hewison Doug Altman William Rosenberg Peter Selby Julien Asselineau Paul Perez Aïssatou Paye Emilie Bessede Cécile Proust-Lima Christiana Naaktgeboren Joris de Groot Anne Rutjes Johannes Reitsma Emmanuel Ogundimu Jonathan Cook Yannick Le Manach Yvonne Vergouwe Romin Pajouheshnia Rolf Groenwold Karen Moons Linda Peelen Daan Nieboer Bavo De Cock Micael J Pencina Ewout W Steyerberg Jennifer Cooper Nick Parsons Chris Stinton Steve Smith Andy Dickens Rachel Jordan Alexandra Enocson David Fitzmaurice Peymane Adab Charles Boachie Gaj Vidmar Karoline Freeman Martin Connock Rachel Court Carl Moons Jessica Harris Andrew Mumford Zoe Plummer Kurtis Lee Barnaby Reeves Chris Rogers Veerle Verheyden Gianni D Angelini Gavin J Murphy Jeremy Huddy Melody Ni Katherine Good Graham Cooke 1Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 2Cochrane Netherlands Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht Netherlands. 234Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 49Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 3Cochrane Dementia and Cognitive Improvement Group University of Oxford Oxford UK. 4EPPI-Centre Department of Social Science University College London London UK. 5Division of Health and Social Care Research King's College London London UK. 6College of Computer and Information Science Northeastern University Boston USA. 13University Hospitals Bristol NHS Foundation Trust School of Social and Community Medicine Bristol UK. 275Institute of Applied Health Research University of Birmingham Birmingham UK. 9Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands. 10School of Social and Community Medicine University of Bristol Bristol UK. 179Institute of Applied Health Research University of Birmingham Birmingham UK. 12Kleijnen Systematic Reviews Ltd York UK. 25Research Institute for Primary Care and Health Sciences Keele University Keele UK. 188Centre for Statistics in Medicine Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford Oxford UK. 191Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands. 237Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands. 18Department of Medical Statistics University Medical Center Göttingen Göttingen Germany. 19Institute for B

[This corrects the article DOI: 10.1186/s41512-016-0001-y.].

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A novel telerobotic method for human-in-the-loop assisted grasping based on intention recognition

A novel telerobotic method for human-in-the-loop assisted gr...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Karan Khokar Redwan Alqasemi Sudeep Sarkar Kyle Reed Rajiv Dubey University of South Florida Tampa Florida USA Research Professor at Center for Assistive Rehabilitation and Robotics Technologies at the University of South Florida Department of Computer Science and Engineering at the University of South Florida Department of Mechanical Engineering at the University of South Florida

In this work, we present a methodology for enabling a robot to identify an object and grasp configuration of interest and assist the human teleoperating the robot, to grasp the object. The identification is carried out in real-time by detecting the motion intention of the human as they are teleoperating the remote robotic arm towards the object and the grasp configuration. Simultaneously, depending on the detected object and grasp configuration, the human user is assisted to translate and orient the remote arm gripper in order to preshape and grasp the object. The complete process occurs with the human teleoperating the arm, and without them having to interact with another interface. Motion intention recognition is carried out by using Hidden Markov Models (HMMs), trained offline by preshape trials performed by a skilled teleoperator. The environment is unstructured and comprises of a number of objects, each with multiple grasp configurations. Experimental tests on healthy human subjects have validated our intention recognition based assistance method. They show that the method allows objects to be grasped and placed 48% faster, and with much ease compared to unassisted teleoperation. Moreover, we have proved that the model for intention recognition, trained by a skilled teleoperator, can be used by novice users to efficiently execute a grasping task in teleoperation.

关键词： Hidden Markov models Vectors Grippers Grasping Teleoperators Training

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Design, implementation and evaluation of a motion control scheme for mobile platforms with high uncertainties

Design, implementation and evaluation of a motion control sc...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Mustafa Mashali Redwan Alqasemi Sudeep Sarkar Rajiv Dubey University of South Florida Tampa Florida USA Research lead at Center for Assistive Rehabilitation and Robotics Technologies at University of South Florida Department of Computer Science and Engineering University of South Florida Department of Mechanical Engineering University of South Florida

In this work, we present a motion control scheme for a robotic mobile platform using low-cost vision sensor to update encoder values. We track the pose of a power wheelchair using wheel encoders along with a Microsoft Kinect camera. Two methods of pose estimation are implemented and tested. These methods are a) encoder-based odometry and b)ICP(Iterative Closest Point)-based updated odometry. We evaluate the performance of each method using precise wheelchair pose ground truth data acquired via a state-of-the-art VICON® system with eight motion capture cameras. Offline data processing is performed to refine the ICP parameters and estimate the covariance matrices of the Kalman filter. The offline data processing results demonstrate that our ICP-based updated odometry has very accurate pose tracking. By implementing our control scheme, the position error is improved by a factor of 15 and the localization orientation error is improved by a factor of 13. In online implementation, there was 4 times improvement for both position and orientation angle estimation. To demonstrate the robustness of our approach, we apply it for online obstacle avoidance. A wheelchair-mounted robotic arm (WMRA) is also included in this platform and will be used for future work on combined mobility and manipulation control with sensor assistance.

关键词： Wheelchairs Robot sensing systems Iterative closest point algorithm Wheels Estimation Motion control Covariance matrices

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ESICM LIVES 2016: part one Milan, Italy. 1-5 October 2016 Abstracts

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INTENSIVE CARE MEDICINE EXPERIMENTAL 2016年第SUPPL 1期4卷 1-1页

作者： [Anonymous] Academic Medical Center University of Amsterdam Amsterdam Netherlands UMCU Utrecht Netherlands Autonomous University of Barcelona Barcelona Spain Hospital São Francisco Xavier Lisbon Portugal CHU Henri Mondor Medical ICU Créteil France Université de Paris Est-Créteil Groupe de Recherche Clinique CARMAS Créteil France Hôpital Tenon APHP Medical and Surgical ICU Paris France Université Paris Diderot Sorbonne Paris Cité UMR 1153 Paris France Interdepartmental Division of Critical Care University of Toronto Toronto Canada University Health Network University of Toronto Critical Care Medicine Toronto Canada University of Milan - Bicocca Health Sciences School of Medicine and Surgery Monza Italy St Michael’s Hospital University of Toronto Anesthesia Toronto Canada CHU d’Angers Medical ICU Angers France Interdepartmental Division of Critical Care University of Toronto Saint Michael’s Hospital and Keenan Research Centre Toronto Canada University of Birmingham Institute for Inflammation and Ageing Birmingham UK University of Sheffield Mathematics and Statistics Help Centre Sheffield UK Heart of England NHS Foundation Trust Intensive Care Medicine Birmingham UK Department of Surgery University Hospitals Birmingham NHS Trust Birmingham UK University Hospitals Birmingham NHS Trust Anaesthesia and Critical Care Medicine Birmingham UK Queen’s University of Belfast Wellcome-Wolfson Institute for Experimental Medicine Belfast UK Royal Victoria Hospital Intensive Care Medicine Belfast UK University of Warwick Warwick Clinical Trials Unit Coventry UK University of Bari ‘Aldo Moro’ Bari Italy Hospital Israelita Albert Einstein São Paulo Brazil Mayo Clinic Jacksonville USA Mahidol University Faculty of Tropical Medicine Bangkok Thailand University Medical Center Utrecht Intensive Care Utrecht Netherlands University Medical Center Utrecht Julius Center for Health Sciences and Primary Care Utrecht Netherlands Academic Medical Center University of Amste

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Sparse motion segmentation using propagation of feature labels

Sparse motion segmentation using propagation of feature labe...

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8th International Conference on computer vision Theory and Applications, VISAPP 2013

作者： Sangi, Pekka Hannuksela, Jari Heikkilä, Janne Silvén, Olli Center for Machine Vision Research Department of Computer Science and Engineering University of Oulu Oulu Finland

ISBN: (纸本)9789898565471

The paper considers the problem of extracting background and foreground motions from image sequences based on the estimated displacements of a small set of image blocks. As a novelty, the uncertainty of local motion estimates is analyzed and exploited in the fitting of parametric object motion models which is done within a competitive framework. Prediction of patch labels is based on the temporal propagation of labeling information from seed points in spatial proximity. Estimates of local displacements are then used to predict the object motions which provide a starting point for iterative refinement. Experiments with both synthesized and real image sequences show the potential of the approach as a tool for tracking based online motion segmentation.

关键词： Uncertainty analysis

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5th International Symposium on Focused Ultrasound Abstracts

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JOURNAL OF THERAPEUTIC ULTRASOUND 2016年第SUPPL 1期4卷 1-1页

作者： [Anonymous] Rambam Health Care Campus Haifa Israel Stanford University Stanford CA USA University of Pennsylvania Philadelphia PA USA The Ohio State University Columbus OH USA University of Virginia Charlottesville VA USA Center for Nanomedicine/Wilmer Eye Institute Johns Hopkins University Baltimore MD USA Columbia University New York NY USA Sunnybrook Health Sciences Centre Toronto ON Canada Sunnybrook Research Institute Toronto ON Canada Clem Jones Centre for Ageing Dementia Research Queensland Brain Institute The University of Queensland St Lucia QLD Australia The University of Queensland Brisbane (St Lucia Campus) QLD Australia University of Leuven Leuven Belgium University of Maryland School of Medicine/Baltimore VAMC Baltimore MD USA Research & Development Service VA Maryland Healthcare System and University of Maryland School of Medicine Baltimore MD USA University of Maryland School of Medicine Baltimore MD USA Brigham and Women’s Hospital Boston MA USA Harvard Medical School Boston MA USA Boston University Boston MA USA National Institutes of Health Bethesda MD USA National Institutes of Health Clinical Center Bethesda MD USA University of Utah Salt Lake City UT USA Focused Ultrasound Foundation Charlottesville VA USA Vanderbilt University Nashville TN USA Georgia Institute of Technology Atlanta GA USA Cleveland Clinic Cleveland OH USA Institut Langevin Ondes et Images ESPCI ParisTech CNRS UMR 7587 INSERM U979 Paris France CENIR ICM CNRS U7225 INSERM U975 Paris France University Children’s Hospital Zurich Zurich Switzerland Jeju National University Jeju Republic of Korea Hospital for Sick Children Toronto ON Canada Centre for Image Guided Innovation and Therapeutic Intervention Toronto ON Canada Philips Healthcare Canada Toronto ON Canada Toronto Western Hospital Toronto ON Canada Thunder Bay Regional Research Institute Thunder Bay ON Canada Incheon St. Mary’s Hospital The Catholic University of Korea Incheon Republic of Korea Departme

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Social Adaptation of Robots for Modulating Self-Organization in Animal Societies

Social Adaptation of Robots for Modulating Self-Organization...

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IEEE International Conference on Self-Adaptive and Self-Organizing Systems Workshops, SASOW

作者： Payam Zahadat Michael Bodi Ziad Salem Frank Bonnet Marcelo Elias De Oliveira Francesco Mondada Karlo Griparic Tomislav Haus Stjepan Bogdan Rob Mills Pedro Mariano Luis Correia Olga Kernbach Serge Kernbach Thomas Schmickl Artificial Life Laboratory of the Department of Zoology Karl-Franzens University Graz Austria Computer Engineering Department Aleppo University Syrian Arab Republic Rbotic Systems Laboratory Swiss Federal Institute of Technology (EPFL) Lausanne Switzerland Ecole Polytechnique Federale de Lausanne Lausanne VD CH Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Zagreb Croatia Universidade de Lisboa Lisboa Lisboa PT Cybertronica Research Research Center of Advanced Robotics and Environmental Science Stuttgart Germany

The goal of the work presented here is to influence the overall behaviour of specific animal societies by integrating computational mechatronic devices (robots) into those societies. To do so, these devices should be accepted by the animals aspart of the society and/or as part of the collectively formed environment. For that, we have developed two sets of robotic hardware for integrating into societies of two different animals: zebra fish and young honeybees. We also developed mechanisms to provide feedback from the behaviours of societies for the controllers of the robotic system. Two different computational methods are then used as the controllers of the robots in simulation and successfully adapted by evolutionary algorithms to influence the simulated animals for desired behaviours. Together, these advances in mechatronic hardware, feedback mechanisms, and controller methodology are laying essential foundations to facilitate experiments on modulating self-organised behaviour in mixed animal -- robot societies.

关键词： Animals Heating Vibrations Robot sensing systems Hardware Biochemistry

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