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检索条件"机构=Computer Vision and Robotics"

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Automated classification and thematic mapping of bacterial mats in the North Sea

Automated classification and thematic mapping of bacterial m...

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Oceans 2013 - Norway

作者： A. S. M. Shihavuddin Nuno Gracias Rafael Garcia Javier Escartin Rolf Birger Pedersen Computer Vision and Robotics (VICOROB) University of Girona (UDG) Equipe de Gosciences Marines Centre for Geobiology University of Bergen

ISBN: (纸本)9781479900022

With the current availability of high quality optical sensors and the advancements of Autonomous Underwater Vehicles (AUVs), it is becoming increasingly accessible to acquire extremely large sets of benthic habitat images. Manual characterization and classification of such large number of images for relevant geological or benthic features can become very difficult and time consuming. This paper presents a novel method for automated segmentation, classification and thematic mapping of bacterial mat from shell chaff and sand, on mosaics created from an image survey on the North Sea. The proposed method uses completed Gabor filter response, grey level co-occurrence matrix (GLCM) and local binary pattern (CLBP) as feature descriptors. After chi-square and Hellinger kernel mapping of feature vector, Probability Density Weighted Mean Distance (PDWMD) is used for classification. Initial segmentation is done using TurboPixels. Our proposed method achieves the highest overall classification accuracy and have moderate execution times compared with the set of methods that are representative of the state-of-the-art in automated classification of seabed images. Our work illustrates that applying automated classification techniques to mosaic composites produces a rapid (in terms of expert annotation time) technique of characterizing benthic areas that can be used to track changes over time.

关键词： thematic mapping North Sea Automation mosaic pattern images methylallyl trisulfide

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Learning monocular reactive UAV control in cluttered natural environments

Learning monocular reactive UAV control in cluttered natural...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Stéphane Ross Narek Melik-Barkhudarov Kumar Shaurya Shankar Andreas Wendel Debadeepta Dey J. Andrew Bagnell Martial Hebert The Robotics Institute Carnegie Mellon University Pittsburgh PA USA Institute for Computer Graphics and Vision Graz University of Technology Austria

ISBN: (纸本)9781467356404

Autonomous navigation for large Unmanned Aerial Vehicles (UAVs) is fairly straight-forward, as expensive sensors and monitoring devices can be employed. In contrast, obstacle avoidance remains a challenging task for Micro Aerial Vehicles (MAVs) which operate at low altitude in cluttered environments. Unlike large vehicles, MAVs can only carry very light sensors, such as cameras, making autonomous navigation through obstacles much more challenging. In this paper, we describe a system that navigates a small quadrotor helicopter autonomously at low altitude through natural forest environments. Using only a single cheap camera to perceive the environment, we are able to maintain a constant velocity of up to 1.5m/s. Given a small set of human pilot demonstrations, we use recent state-of-the-art imitation learning techniques to train a controller that can avoid trees by adapting the MAVs heading. We demonstrate the performance of our system in a more controlled environment indoors, and in real natural forest environments outdoors.

关键词： Training Cameras Trajectory Optical imaging Sensors Visualization Vegetation

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Match Elimination using Cycle Basis in Underwater Optical Mapping

Match Elimination using Cycle Basis in Underwater Optical Ma...

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Oceans 2013 - Norway

作者： Armagan Elibol Jinwhan Kim Son-Cheol Yu Nuno Gracias Rafael Garcia Division of Ocean Systems Engineering Dept. of Creative IT Excellence Eng. POSTECH Computer Vision and Robotics Group University of Girona

ISBN: (纸本)9781479900022

The use of image mosaicing methods for underwater optical mapping has become very popular owing to the rapid progress in obtaining optical data using robotic platforms. In order to obtain globally consistent mosaics, one of the essential steps is global alignment for finding best image registration parameters, which employs non-linear optimisation methods to minimise the error metric defined over correspondences detected between overlapping image pairs. In this paper, we propose a method that uses graph theory principles to reduce the total number of overlapping image pairs used in the global alignment process without degrading the final mosaic quality. This reduction allows for obtaining image mosaics with reduced computational cost and time. The method is validated through two experiments that involve challenging underwater datasets.

关键词： global alignment image stitching Underwater image registration Graph theory optical Mosaic mosaic pattern MAPPING(MATHEMATICAL)

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Turnout detection and classification using a modified HOG and template matching

Turnout detection and classification using a modified HOG an...

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International IEEE Conference on Intelligent Transportation Systems

作者： Jorge Corsino Espino Bogdan Stanciulescu Mathematics and Computer Vision Science SIEMENS S.A.S. Infrastructure & Cities Division Mobility and Logistics Robotics center Mines-ParisTech

ISBN: (纸本)9781479929153

This paper presents a railway track and turnout detection and turnout classification algorithm. The railway track extraction is based on an edge detection using the width of the rolling pads. This edge detection scheme is then used as an input to the RANSAC algorithm to determine the model of the rails knowing their gauge. The turnout detection scheme is based on the Histogram of Oriented Gradient (HOG) and Template Matching (TM). The turnout classification is based on HOG. The detection results show (i) reliable performance for our railway track extraction scheme;(ii) a correction rate of 97.31 percent for the turnout detection scheme using a Support Vector Machine (SVM) classifier. The turnout classification has correction rate of 98.72 percent using SVM.

关键词： Railway track TEMPLATE MATCHING Edge detection Support Vector Network turnout histograms Railway Rail ROLLED SCROLL

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Pedestrian detection based on LIDAR-driven sliding window and relational parts-based detection

Pedestrian detection based on LIDAR-driven sliding window an...

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IEEE Symposium on Intelligent Vehicle

作者： Luciano Oliveira Urbano Nunes Intelligent Vision Research Laboratory Federal University Bahia Brazil Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Portugal

The most standard image object detectors are usually comprised of one or multiple feature extractors or classifiers within a sliding window framework. Nevertheless, this type of approach has demonstrated a very limited performance under datasets of cluttered scenes and real life situations. To tackle these issues, LIDAR space is exploited here in order to detect 2D objects in 3D space, avoiding all the inherent problems of regular sliding window techniques. Additionally, we propose a relational parts-based pedestrian detection in a probabilistic non-iid framework. With the proposed framework, we have achieved state-of-the-art performance in a pedestrian dataset gathered in a challenging urban scenario. The proposed system demonstrated superior performance in comparison with pure sliding-window-based image detectors.

关键词： Detectors Laser radar Feature extraction Support vector machines Training Probabilistic logic Vectors

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Rapid disparity prediction for dynamic scenes

Rapid disparity prediction for dynamic scenes

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9th International Symposium on Advances in Visual Computing, ISVC 2013

作者： Jiang, Jun Cheng, Jun Chen, Baowen Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Chinese University of Hong Kong Hong Kong Hong Kong Shsenzhen Institute of Information Technology China Guangdong Provincial Key Laboratory of Robotics and Intelligent System China Shenzhen Key Laboratory of Computer Vision and Pattern Recognition China

ISBN: (纸本)9783642419133

Real-time 3D sensing plays a critical role in robotic navigation, video surveillance and human-computer interaction, etc. When computing 3D structures of dynamic scenes from stereo sequences, spatiotemporal stereo and scene flow methods can produce temporally coherent disparity. However, most existing methods do not utilize the previous disparity map sufficiently to compute the next disparity map, and the searching space of correspondences limits the speed of disparity computation for each image pair. This paper proposes an effective scheme to predict disparity maps from stereo sequences. In particular, we apply a robust 3D registration algorithm based on the angular-invariant feature to estimate the ego-motion of the stereo rig between consecutive frames, and present the transformation between consecutive disparity maps. The scheme can produce a sequence of temporally coherent disparity maps rapidly. We apply the new scheme to real outdoor scenes, and thorough empirical studies indicate the effectiveness of the new scheme for practical applications. © 2013 Springer-Verlag.

关键词： Human computer interaction

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Fuzzy Decision Support System for the Determination of the Set Points of Relevant Variables in the Virgin Olive Oil Elaboration Process

Fuzzy Decision Support System for the Determination of the S...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： P. Cano Marchal D. Martinez Gila J. Gámez Garcia J. Gómez Ortega Robotics Automation and Computer Vision Group University of Jaén. Agrifood Campus of International Excellence (ceiA3). Jaén Spain

ISBN: (纸本)9781479906505

The virgin olive oil elaboration process (VOOEP) is an industrial process whose control relies heavily in the knowledge of experts. In this paper, the basis of a fuzzy expert system for the determination of the set points of the VOOEP which uses inputs from the expert operator is presented, and a system is constructed and validated based on the knowledge of expert operators of the process. The expert system is built based on the decomposition of the original problem into three sub-problems, deriving a subsystem for each of them. Besides, a notion of maximum attainable quality estimate and a paste preparation variable are introduced.

关键词： Olive Oil Fuzzy Expert System fuzzy expert system Olive Oil decision support systems Set of points Professional personnel accuracy class Caste determination Sex Determination Processes Industrial processes original problem Expert System SUB-SYSTEM

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From D-H to Inverse Kinematics: A Fast Numerical Solution for General Robotic Manipulators Using Parallel Processing

From D-H to Inverse Kinematics: A Fast Numerical Solution fo...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Siavash Farzan G. N. DeSouza Vision-Guided and Intelligent Robotics Lab - ViGIR Department of Electrical and Computer Engineering University of Missouri 349 Eng. Building West Columbia MO 6521

ISBN: (纸本)9781467363563

We propose a robust and fast solution for the inverse kinematic problem of general serial manipulators - i.e. any number and any combination of revolute and prismatic joints. The algorithm only requires the Denavit-Hartenberg (D-H) representation of the robot as input and no training or robot-dependent optimization function is needed. In order to handle singularities and to overcome the possibility of multiple paths in redundant robots, our approach relies on the computation of multiple (parallel) numerical estimations of the inverse Jacobian while it selects the current best path to the desire configuration of the end-effector. But unlike other iterative methods, our method achieves sub-millimeter accuracy in 20.48ms in average. The algorithm was implemented in C/C++ using 16 POSIX threads, and it can be easily expanded to use more threads and/or many-core GPUs. We demonstrate the high accuracy and the real-time performance of our method by testing it with five different robots, at both non-singular and singular configurations, including a 7-DoF redundant robot.

关键词： Inverse Kinematics Inverse Jacobian Serial Manipulators Denavit-Hartenberg PARALLEL PROCESSING (computerS) Redundant robot Manipulators Robot Manipulator D/H Robot inverse kinematics iterative methods Fasting Test Method prismatic joint

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Learning compact parameterized skills with a single regression

Learning compact parameterized skills with a single regressi...

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IEEE-RAS International Conference on Humanoid Robots

作者： Freek Stulp Gennaro Raiola Antoine Hoarau Serena Ivaldi Olivier Sigaud FLOWERS Team INRIA Bordeaux Sud-Ouest Talence France Robotics and Computer Vision ENSTA-ParisTech Paris France Pal Robotics S.L. Barcelona Spain ISIR Université Pierre Marie Curie Paris France

One of the long-term challenges of programming by demonstration is achieving generality, i.e. automatically adapting the reproduced behavior to novel situations. A common approach for achieving generality is to learn parameterizable skills from multiple demonstrations for different situations. In this paper, we generalize recent approaches on learning parameterizable skills based on dynamical movement primitives (DMPs), such that task parameters are also passed as inputs to the function approximator of the DMP. This leads to a more general, flexible, and compact representation of parameterizable skills, as demonstrated by our empirical evaluation on the iCub and Meka humanoid robots.

关键词： Trajectory Training Kernel Vectors Robots Visualization Shape

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Caging Complex Objects with Geodesic Balls

Caging Complex Objects with Geodesic Balls

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Dmitry Zarubin Florian T. Pokorny Marc Toussaint Danica Kragic Machine Learning and Robotics Lab Universitat Stuttgart Stuttgart Germany Centre for Autonomous Systems Computer Vision and Active Perception Lab School of Computer Science and Communication KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467363563

This paper proposes a novel approach for the synthesis of grasps of objects whose geometry can be observed only in the presence of noise. We focus in particular on the problem of generating caging grasps with a realistic robot hand simulation and show that our method can generate such grasps even on complex objects. We introduce the idea of using geodesic balls on the object's surface in order to approximate the maximal contact surface between a robotic hand and an object. We define two types of heuristics which extract information from approximate geodesic balls in order to identify areas on an object that can likely be used to generate a caging grasp. Our heuristics are based on two scoring functions. The first uses winding angles measuring how much a geodesic ball on the surface winds around a dominant axis, while the second explores using the total discrete Gaussian curvature of a geodesic ball to rank potential caging postures. We evaluate our approach with respect to variations in hand kinematics, for a selection of complex real-world objects and with respect to its robustness to noise.

关键词： Caging Complex Objects Geodesic Balls Gaussian curvature

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