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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Eshed Ohn-Bar Ashish Tawari Sujitha Martin Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego

Automotive systems provide a unique opportunity for mobile vision technologies to improve road safety by understanding and monitoring the driver. In this work, we propose a real-time framework for early detection of driver maneuvers. The implications of this study would allow for better behavior prediction, and therefore the development of more efficient advanced driver assistance and warning systems. Cues are extracted from an array of sensors observing the driver (head, hand, and foot), the environment (lane and surrounding vehicles), and the ego-vehicle state (speed, steering angle, etc.). Evaluation is performed on a real-world dataset with overtaking maneuvers, showing promising results. In order to gain better insight into the processes that characterize driver behavior, temporally discriminative cues are studied and visualized.

关键词： Vehicles Sensors Cameras Foot Histograms Radar tracking Vehicle dynamics

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Fast and Robust Object Detection Using Visual Subcategories

Fast and Robust Object Detection Using Visual Subcategories

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Eshed Ohn-Bar Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego

Object classes generally contain large intra-class variation, which poses a challenge to object detection schemes. In this work, we study visual subcategorization as a means of capturing appearance variation. First, training data is clustered using color and gradient features. Second, the clustering is used to learn an ensemble of models that capture visual variation due to varying orientation, truncation, and occlusion degree. Fast object detection is achieved with integral image features and pixel lookup features. The framework is studied in the context of vehicle detection on the challenging KITTI dataset.

关键词： Vehicles Visualization Feature extraction Vehicle detection Image color analysis Support vector machines Detectors

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Breast masses identification through pixel-based texture classification 1

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12th International Workshop on Breast Imaging, IWDM 2014

作者： Torrents-Barrena, Jordina Puig, Domenec Ferre, Maria Melendez, Jaime Diez-Presa, Lorena Arenas, Meritxell Martí, Joan Department of Computer Engineering and Mathematics University Rovira I Virgili Spain Department of Radiology Radboud University Medical Center Netherlands Radiotherapic Oncology Research Group Hospital Universitari Sant Joan de Reus Spain Computer Vision and Robotics Research Institute University of Girona Spain

ISBN: (数字)9783319078878

ISBN: (纸本)9783319078861

Mammographic image analysis plays an important role in computer-aided breast cancer diagnosis. To improve the existing knowledge, this paper proposes a new efficient pixel-based methodology for tumor vs non-tumor classification. The proposed method firstly computes a Gabor feature pool from the mammogram. This feature set is calculated through multi-sized evaluation windows applied to the probabilistic distribution moments, in order to improve the accuracy of the whole system. To deal with a high dimensional data space and a large amount of features, we apply both a linear and non-linear pixel classification stage by using Support Vector Machines (SVMs). The randomness is encoded when training each SVM using randomly sample sets and, in consequence, randomly selected features from the whole feature bank obtained in the first stage. The proposed method has been validated using real mammographic images from well-known databases and its effectiveness is demonstrated in the experimental section. © 2014 Springer International Publishing.

关键词： Pixels

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Active Range-Only Beacon Localization for AUV Homing

Active Range-Only Beacon Localization for AUV Homing

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Guillem Vallicrosa Pere Ridao David Ribas Albert Palomer Underwater Robotics Research Center (CIRS) Computer Vision and Robotics Institute (VICOROB) Universitat de Girona 17071 Girona Spain

ISBN: (纸本)9781479969357

This paper presents a solution to the 3D Range-Only beacon localization problem using a Sum of Gaussians (SOG) filter together with an Active Localization method, which is based on the minimization of the beacon position uncertainty, in order to ensure the problem observability and a fast convergence. The method is applied to autonomously locate a subsea panel and home to it in order to establish visual contact to later launch a visual servoing based docking task. The method is demonstrated through field experiments in a harbor environment with an Autonomous Underwater Vehicle (AUV) including Ultra-Short Baseline (USBL) ground truth information.

关键词： Autonomous underwater vehicles field experimentation Localization method

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HEAD POSE TRACKING FOR IMMERSIVE APPLICATIONS

HEAD POSE TRACKING FOR IMMERSIVE APPLICATIONS

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IEEE International Conference on Image Processing

作者： Pedro Henriquez Oscar Higuera Bogdan J. Matuszewski Robotics and Computer Vision Research Laboratory School of Computing Engineering and Physical Sciences University of Central Lancashire

ISBN: (纸本)9781479957521

The paper describes a 3D head pose tracking system designed for immersive applications. The proposed system is based on a random forest's head detection and pose regression model. The main novel contributions include the application, in immersive technologies, of a head tracker using a range data sensor, the Kalman filter and the random forest, with automatic detection of outliers and handling of the missing data. The envisaged applications of the proposed system include data normalization and data acquisition from remote locations in real-time. The latter is described in detail by integrating 3 degrees of freedom robotic camera head with the proposed head tracker. In this instance the proposed non-contact head tracking system is used to control the robotic camera by replicating measured operator's head motion to improve his/her spatial awareness and sense of immersion, with the captured video shown on a head mounted display. The experimental section includes accuracy and robustness analysis. The system's robustness is examined with respect to the head pose outliers and the missing head detections. The effects of the presence of the head mounted displays on the performance of the system is also assessed. Additionally a brief discussion of operators' psycho-physical perception test is also included.

关键词： Head pose tracking Kalman filter Spatial Immersion

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Autonomous I-AUV Docking for Fixed-base Manipulation

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IFAC Proceedings Volumes 2014年第3期47卷 12160-12165页

作者： Narcís Palomeras Pere Ridao David Ribas Guillem Vallicrosa Computer Vision and Robotics Research Institute Scientific and Technological Park of the University of Girona CIRS Building C/ Pic de Peguera CO 17071 Girona Catalonia - Spain

While commercially available autonomous underwater vehicles (AUVs) are routinely used in survey missions, a new set of applications exist demanding intervention capabilities. This is the case, for instance, of the maintenance of permanent underwater observatories or submerged oil wells. These tasks, currently undertaken by remotely operated vehicles (ROVs), can be automated using intervention AUVs (I-AUVs) reducing their complexity and costs. The TRITON spanish funded project proposes the use of light I-AUV for autonomous intervention tasks, such as valve turning or connector pluging/unpluging, in adapted sub-sea infrastructures. To this aim, this paper presents the design and implementation of an I-AUV-friendly sub-sea docking panel, as well as the vision-based autonomous docking procedure for the Girona 500 lightweight I-AUV. The panel implements a funnel-based docking method for passive accommodation. It also includes a T valve and a custom designed hot stab connector. Once docked, the I-AUV and the panel become rigid and basic fixed-base manipulation strategies can be used for manipulation.

关键词： Autonomous vehicles Marine systems Robot navigation Robot vision Robot control Robotic manipulators

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Intervention AUVs: The next challenge 19

Intervention AUVs: The next challenge

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19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014

作者： Ridao, Pere Carreras, Marc Ribas, David Sanz, Pedro J. Oliver, Gabriel Computer Vision and Robotics Research Institute Scientific and Technological Park University of Girona CIRS Building C/Pic de Peguera Girona CataloniaCO 17071 Spain Av. Vicent Sos Banyat S/N Castelln12006 Spain Cra. Valldemossa Palma07122 Spain

ISBN: (纸本)9783902823625

While commercially available AUVs are routinely used in survey missions, a new set of applications exists which clearly demand intervention capabilities. The maintenance of: permanent observatories underwater;submerged oil wells;cabled sensor networks;pipes;and the deployment and recovery of benthic stations are but a few of them. These tasks are addressed nowadays using manned submersibles or work-class ROVs, equipped with teleoperated arms under human supervision. Although researchers have recently opened the door to future I-AUVs, a long path is still necessary to pave the way to underwater intervention applications performed in an autonomous way. This paper reviews the evolution timeline in autonomous underwater intervention systems. Milestone projects in the state of the art are reviewed, highlighting their principal contributions to the field. To the best of the authors knowledge only three vehicles have demonstrated some autonomous intervention capabilities so far: ALIVE, SAUVIM and GIRONA 500 I-AUV. Next, GIRONA 500 I-AUV is presented and its software architecture discussed. Recent results in different scenarios are reported: 1) Valve turning and connector plugging/unplugging while docked to a sub-sea panel, 2) Free floating valve turning using learning by demonstration, and 3) Free floating multipurpose multisensory based object recovery. The paper ends discussing the lessons learned so far and presenting the authors view of the future. © IFAC.

关键词： Autonomous underwater vehicles

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Control Strategies for a Humanoid Robot to Drive and then Egress a Utility Vehicle for Remote Approach

Control Strategies for a Humanoid Robot to Drive and then Eg...

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IEEE-RAS International Conference on Humanoid Robots

作者： Hyobin Jeong Jaesung Oh Mingeuk Kim Kyungdon Joo In So Kweon Jun-Ho Oh Humanoid Research Center School of Mechanical Aerospace & Systems Engineering Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Robotics and Computer Vision Laboratory School of Mechanical Aerospace & Systems Engineering Department of Electrical Engineering Korea Advanced Institute of Science and Technology Department of Electrical Engineering KAIST

ISBN: (纸本)9781479968862

This paper proposes strategies for the driving and egress of a vehicle with a humanoid robot. To drive the vehicle, the RANSAC method was used to detect obstacles, and the Wagon model was used to control the steering and velocity of the vehicle with only a limited number of sensors which were installed on the humanoid robot. Additionally, a manual teleoperating method was used with the lane projection technique. For the egress motion, gain override and the Cartesian position/force control technique were used to interact with the vehicle structure. To overcome the disadvantages of a highly geared manipulator, a special technique was used that included modelled friction compensation and a non-complementary switching mode. DRC-HUBO+ used the proposed method to perform a vehicle driving and egress task in the DRC finals 2015.

关键词： Humanoid robots EGRESS vehicle Vehicle driving Automobile driving UTILITY VEHICLES control strategy friction compensation DRIVES Steering

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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