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检索条件"任意字段=Conference on Intelligent Robots and Computer Vision XXIX - Algorithms and Techniques"

共 373 条记录，以下是311-320 订阅

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3D robot perception with Point Cloud Library

引用

ROBOTICS AND AUTONOMOUS SYSTEMS 2016年 78卷 97-99页

作者： Munaro, Matteo Rusu, Radu B. Menegatti, Emanuele Univ Padua Sch Engn Dept Informat Engn DEI Intelligent Autonomous Syst Lab Via Gradenigo 6-a I-35131 Padua Italy Open Percept Inc 68 Willow Rd Menlo Pk CA 94025 USA

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Automatic restoration of underwater monocular sequences of images

Automatic restoration of underwater monocular sequences of i...

引用

IEEE/RSJ International conference on intelligent robots and Systems, IROS 2015

作者： Drews, Paulo Nascimento, Erickson R. Campos, Mario F. M. Elfes, Alberto Department of Computer Science of the Universidade Federal de Minas Gerais - UFMG Belo Horizonte Brazil Paulo Drews-Jr is Also with Centro de Ciências Computacionais- C3 Univ. Federal Do Rio Grande - FURG Rio Grande Brazil Autonomous System Program - ASP CSIRO Pullenvale Australia

ISBN: (纸本)9781479999941

Underwater environments present a considerable challenge for computer vision, since water is a scattering medium with substantial light absorption characteristics which is made even more severe by turbidity. This poses significant problems for visual underwater navigation, object detection, tracking and recognition. Previous works tackle the problem by using unreliable priors or expensive and complex devices. This paper adopts a physical underwater light attenuation model which is used to enhance the quality of images and enable the applicability of traditional computer vision techniques images acquired from underwater scenes. The proposed method simultaneously estimates the attenuation parameter of the medium and the depth map of the scene to compute the image irradiance thus reducing the effect of the medium in the images. Our approach is based on a novel optical flow method, which is capable of dealing with scattering media, and a new technique that robustly estimates the medium parameters. Combined with structure-from-motion techniques, the depth map is estimated and a model-based restoration is performed. The method was tested both with simulated and real sequences of images. The experimental images were acquired with a camera mounted on a Remotely Operated Vehicle (ROV) navigating in a naturally lit, shallow seawater. The results show that the proposed technique allows for substantial restoration of the images, thereby improving the ability to identify and match features, which in turn is an essential step for other computer vision algorithms such as object detection and tracking, and autonomous navigation. © 2015 IEEE.

关键词： Image enhancement

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A General Model and Calibration Method for Spherical Stereoscopic vision

A General Model and Calibration Method for Spherical Stereos...

引用

conference on intelligent robots and computer vision xxix - algorithms and techniques

作者： Feng, Weijia Roning, Juha Kannala, Juho Zong, Xiaoning Zhang, Baofeng Tianjin Univ State Key Lab Precis Measuring Technol & Instrume Tianjin 300072 Peoples R China Oulu Univ Infotech Oulu Oulu Finland Oulu Univ Elect & Informat Engn Dept Oulu Finland

ISBN: (纸本)9780819489487

In geometric calibration of stereoscopic cameras the object is to determine a set of parameters which describe the mapping from 3D reference coordinates to 2D image coordinates, and indicate the geometric relationships between the cameras. While various methods for stereo cameras with ordinary lenses can be found from the literature, stereoscopic vision with extremely wide angle lenses has been much less discussed. Spherical stereoscopic vision is more and more convenient in computer vision applications. However, its use for 3D measurement purposes is limited by the lack of an accurate, general, and easy-to-use calibration procedure. Hence, we present a geometric model for spherical stereoscopic vision equipped by extremely wide angle lenses. Then, a corresponding generic mathematical model is built. Method for calibration the parameters of the mathematical model is proposed. This paper shows practical results from the calibration of two high quality panomorph lenses mounted on cameras with 2048x1536 resolutions. Here, the stereoscopic vision system is flexible, the position and orientation of the cameras can be adjusted randomly. The calibration results include interior orientation, exterior orientation and the geometric relationships between the two cameras. The achieved level of calibration accuracy is very satisfying.

关键词： spherical stereoscopic vision panomorph lens general geometric and mathematical model parameter calibration

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Fast 3D object reconstruction using trinocular vision and structured light

Fast 3D object reconstruction using trinocular vision and st...

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Proceedings of the 1998 conference on intelligent robots and computer vision XVII: algorithms, techniques, and Active vision

作者： Hamdan, H.M. Hemayed, E.E. Farag, A.A. Univ of Louisville Louisville United States

For faithful 3-D reconstruction of objects with smooth surfaces, stereo vision techniques rely heavily on the surface texture. However, most of the real life objects lack this feature. To `sharpen' the textural content of visual surfaces, a structured-light sensing configuration has been used. This technique can be used to enhance the features used in solving the correspondence problem in computational stereo vision. A light pattern is projected to encode the smooth surface of the object. The observed light pattern is then used to compute surface properties. We present a simple design for a trinocular vision system with structured light using off-the-shelf components. The processing pipeline of the system consists of four stages. First, the light pattern is detected in the captured images. Second, the pattern is skeletonized using connected component labeling. Third, a maximum-weighted bipartite technique is used to do the matching. Finally, a global surface fitting technique is used to integrate the reconstruction from different views in one frame and fit a mesh of triangles to the integrated data. Results using real images are promising. The advantages of this system lie in its design simplicity, low cost and the potential for fast and parallel implementation.

关键词： computer vision

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Teaching robots to Predict Human Motion

Teaching Robots to Predict Human Motion

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25th IEEE/RSJ International conference on intelligent robots and Systems (IROS)

作者： Gui, Liang-Yan Zhang, Kevin Wang, Yu-Xiong Liang, Xiaodan Moura, Jose M. F. Veloso, Manuela Carnegie Mellon Univ Dept Elect & Comp Engn Pittsburgh PA 15213 USA Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA Carnegie Mellon Univ Machine Learning Dept Pittsburgh PA 15213 USA

ISBN: (纸本)9781538680940

Teaching a robot to predict and mimic how a human moves or acts in the near future by observing a series of historical human movements is a crucial first step in human-robot interaction and collaboration. In this paper, we instrument a robot with such a prediction ability by leveraging recent deep learning and computer vision techniques. First, our system takes images from the robot camera as input to produce the corresponding human skeleton based on real-time human pose estimation obtained with the OpenPose library. Then, conditioning on this historical sequence, the robot forecasts plausible motion through a motion predictor, generating a corresponding demonstration. Because of a lack of high-level fidelity validation, existing forecasting algorithms suffer from error accumulation and inaccurate prediction. Inspired by generative adversarial networks (GANs), we introduce a global discriminator that examines whether the predicted sequence is smooth and realistic. Our resulting motion GAN model achieves superior prediction performance to state-of-the-art approaches when evaluated on the standard H3.6M dataset. Based on this motion GAN model, the robot demonstrates its ability to replay the predicted motion in a human-like manner when interacting with a person.

关键词： robots Gallium nitride Generative adversarial networks Predictive models Cameras Skeleton Decoding

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PRoViScout - a Planetary Scouting Rover Demonstrator

PRoViScout - a Planetary Scouting Rover Demonstrator

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conference on intelligent robots and computer vision xxix - algorithms and techniques

作者： Paar, Gerhard Woods, Mark Gimkiewicz, Christiane Labrosse, Frederic Medina, Alberto Tyler, Laurence Barnes, David P. Fritz, Gerald Kapellos, Konstantinos JOANNEUM RES Steyrergasse 17 A-8010 Graz Austria SciSys Bristol Avon BS4 5SS England CSEM Zurich Ctr CH-8005 Zurich Switzerland Aberystwyth Univ Aberystwyth Dyfed Wales GMVc Isaac Newton Tres Cantos 28760 Spain TRASYS Space B-1560 Hoeilaart Belgium

ISBN: (纸本)9780819489487

Mobile systems exploring Planetary surfaces in future will require more autonomy than today. The EU FP7-SPACE Project ProViScout (2010-2012) establishes the building blocks of such autonomous exploration systems in terms of robotics vision by a decision-based combination of navigation and scientific target selection, and integrates them into a framework ready for and exposed to field demonstration. The PRoViScout on-board system consists of mission management components such as an Executive, a Mars Mission On-Board Planner and Scheduler, a Science Assessment Module, and Navigation & vision Processing modules. The platform hardware consists of the rover with the sensors and pointing devices. We report on the major building blocks and their functions & interfaces, emphasizing on the computer vision parts such as image acquisition (using a novel zoomed 3D-Time-of-Flight & RGB camera), mapping from 3D-TOF data, panoramic image & stereo reconstruction, hazard and slope maps, visual odometry and the recognition of potential scientifically interesting targets.

关键词： Planetary rover autonomous navigation robotic vision planning 3D-TOF Mars exploration decision making planetary science science interest

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Path planning for mobile robot using sonar map and neural network

Path planning for mobile robot using sonar map and neural ne...

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Proceedings of the 1998 conference on intelligent robots and computer vision XVII: algorithms, techniques, and Active vision

作者： Cao, Jin Chiang, Wen-chuan Mundhenk, T.Nathan Halls, Ernest L. Univ of Cincinnati Cincinnati United States

The purpose of this paper is to present a new approach for path planing of a mobile robot in static outdoor environments. A simple sensor model is developed for fast acquisition of environment information. The obstacle avoidance system is based on a micro-controller interfaced with multiple ultrasonic transducers with a rotating motor. Using sonar readings and environment knowledge, a local map based on weight evaluation function is built for the robot path planing. The path planner finds the local optimal path using the A* search algorithm. The robot is trained to learn a goal-directed task under adequate supervision. The simulation experiments show that a robot, utilizing our neural network scheme, can learn tasks of obstacle avoidance in the work space of a certain geometrical complexity. The result shows that the proposed algorithm can be efficiently implemented in an outdoor environment.

关键词： Mobile robots

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Range detection for AGV using a rotating sonar sensor

Range detection for AGV using a rotating sonar sensor

引用

Proceedings of the 1998 conference on intelligent robots and computer vision XVII: algorithms, techniques, and Active vision

作者： Chiang, Wen-chuan Ramamurthy, Dhyana Chandra Mundhenk, T.Nathan Hall, Ernest L. Univ of Cincinnati Cincinnati OH United States

A single rotating sonar element is used with a restricted angle of sweep to obtain readings to develop a range map for the unobstructed path of an autonomous guided vehicle (AGV). A Polaroid ultrasound transducer element is mounted on a micromotor with an encoder feedback. The motion of this motor is controlled using a Galil DMC 1000 motion control board. The encoder is interfaced with the DMC 1000 board using an intermediate IMC 1100 break-out board. By adjusting the parameters of the Polaroid element, it is possible to obtain range readings at known angles with respect to the center of the robot. The readings are mapped to obtain a range map of the unobstructed path in front of the robot. The idea can be extended to a 360 degree mapping by changing the assembly level programming on the Galil Motion control board. Such a system would be compact and reliable over a range of environments and AGV applications.

关键词： computer vision

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Reexamining Indoor Mobile robots from a Cognitive Perspective 5

Reexamining Indoor Mobile Robots from a Cognitive Perspectiv...

引用

5th International conference on Robotics and computer vision, ICRCV 2023

作者： Song, Fei Li, Jinyu Tang, Fengzhen Tang, Yandong Si, Bailu State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China School of Systems Science Beijing Normal University Beijing China

ISBN: (纸本)9798350326369

The field of traditional mobile robot navigation has undergone a gradual transformation, evolving into a standardized and procedural research domain. Through a fresh cognitive perspective on this navigation process, a bridge emerges between robotic researchers and cognitive neuroscientists, thereby fostering the growth of interdisciplinary exploration. This article meticulously examines three pivotal phases of robot navigation: information acquisition, simultaneous localization and mapping (SLAM), and path planning. These phases are intricately linked to pertinent cognitive research. Furthermore, a comprehensive survey of existing biomimetic and neuromorphic algorithms is presented, highlighting their applications in augmenting robot navigation capabilities. Ultimately, this article charts a visionary course for the future of robot navigation, envisioning its potential in facilitating more intelligent and efficient navigation techniques. © 2023 IEEE.

关键词： Navigation

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Modeling active vision during smooth pursuit of a robotic eye 33

Modeling active vision during smooth pursuit of a robotic ey...

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33rd intelligent robots and computer vision: algorithms and techniques conference

作者： Turski, Jacek University of Houston-Downtown HoustonTX United States

The computational framework, based on the conformal camera, is developedfor processingvisual information during smooth pursuit movements of a robotic eye. During smooth pursuit, the image of the tracked object remains nearly stationary while the image of a stationary background sweeps across the image plane of the camera. The background's image transformation derived in the second-order approximation enable the anticipation of the perceptual outcome of the camera pursuit. This can be used to support the correct visual information of the moving object in front of the stationary background, These results complement the author's previous study on the predictive image processing for visual stability during the conformalcamera movementsresembling primate's saccadic eye rotations. The visual information processing algorithms that can support visual stability during smooth pursuit and saccadic movements of an anthropomorphic robotic camera are needed for an autonomous robot efficient interactions with the real world, in real time. © 2016 Society for Imaging Science and Technology.

关键词： Cameras

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