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

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Defect Detection in Porcelain Industry based on Deep Learning techniques 19

Defect Detection in Porcelain Industry based on Deep Learnin...

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19th International Symposium on Symbolic and Numeric algorithms for Scientific Computing (SYNASC)

作者： Birlutiu, Adriana Burlacu, Adrian Kadar, Manuella Onita, Daniela 1 Decembrie 1918 Univ Alba Iulia Gabriel Bethlen 5 Alba Iulia 510009 Romania Gheorghe Asachi Tech Univ Iasi Bd Prof Dimitrie Mangeron 67 Iasi 700050 Romania

ISBN: (纸本)9781538626269

This paper presents an automated defect management system based on machine learning and computer vision that detects and quantifies different types of defects in porcelain products. The system is developed in collaboration with an industrial porcelain producer and integrates robots, artificial vision and machine learning. At present, in most of the companies involved in the porcelain industry, defect detection is performed manually by employees. An intelligent system for product monitoring and defect detection is very much needed. Our proposed system is implemented through a convolutional neural network which analyzes images of the products and predicts if the product is defective or not. Experimental evaluation on an image data set acquired at the industrial partner shows promising results. The proposed architecture will finally have a positive economic impact for the company by optimizing the production flow and reducing the production costs.

关键词： deep learning defects porcelain

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Hybrid Solution for Person Following Robot System

Hybrid Solution for Person Following Robot System

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作者： Cohen Shalom Judah San Diego State University Computer Science

学位级别：M.S.

The thesis is a further contribution to the area of robotic person following that has been an on-going research at the intelligent robots and Systems Laboratory. The goal of this research was to enhance the vision based robotic person following with the accelerometer and gyroscope using a standard cell-phone device. The signals that are generated by the cell phone on the person while the person walks provide information about the number of steps and the direction of the motion of the person. These sensor values are sent through a personal wireless network to the robot computer. The received signals are process using various signal processing techniques including the Kalman filter and peak detection algorithms to extract the number of steps taken by the person and the direction of the motion of the person. The processed signals are then used by a fuzzy logic algorithm to determine the distance between the robot and the person, thus identifying the location of the person with respect to the robot. The robot then follows the person based on the estimated location of the person. The person is also identified by a vision system as complementary and secondary method for person detection. The vision-based system develops a number of morphological operations to detect the person and segment it from the scene and other objects in the image. The complete system has been implemented on a Segway robot platform, and a number of tests have been performed, these tests include walking of different persons and recording the distances travelled, the estimation of the person's location by the system and its comparison with the actual recorded measurements. The results show that in majority of cases the system is successful in person following in simple environments. The thesis concludes by outlining a number of improvements that can be made to the system for more robust operation.

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Defect Detection in Porcelain Industry Based on Deep Learning techniques

Defect Detection in Porcelain Industry Based on Deep Learnin...

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International Symposium on Symbolic and Numeric algorithms for Scientific Computing (SYNASC)

作者： Adriana Birlutiu Adrian Burlacu Manuella Kadar Daniela Onita “Decembrie 1918” University of Alba Iulia Alba Iulia Romania “Gheorghe Asachi” Technical University of Iasi Iasi Romania

ISBN: (纸本)9781538626276

关键词： Feature extraction Inspection Porcelain Production Industries computer vision

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Autonomous flight and vision-based target tracking for a flapping-wing MAV

Autonomous flight and vision-based target tracking for a fla...

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2016 IEEE/RSJ International Conference on intelligent robots and Systems, IROS 2016

作者： Ryu, Seungwan Kwon, Ukjin Jin Kim, H. Department of Mechanical and Aerospace Engineering Korea Republic of Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of

ISBN: (纸本)9781509037629

In this paper, we design an autonomous flight controller for height regulation and bang-bang controller for directional control of a light-weight flapping-wing micro air vehicle (FWMAV) with limited payload. We also present autonomous vision-based target tracking for a FWMAV equipped with a low-cost and light-weight first person view (FPV) camera. We construct a ground station, integrated with control and vision algorithms, which performs the image processing and the computation of control inputs based on the acquired state variables from motion capture system. In addition, we employ a vision algorithm for a low-quality camera to detect a static target with the discussions on the techniques to improve the reliability of visual detection. Experimental results show satisfactory flight performance, achieving the height regulation and directional control, and autonomous vision-based target tracking. © 2016 IEEE.

关键词： Cameras

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3D robot perception with Point Cloud Library

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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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The 23RD annual intelligent ground vehicle competition: Building engineering students into robotists 33

The 23RD annual intelligent ground vehicle competition: Buil...

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

作者： Theisen, Bernard L. U.S. Army TARDEC 6501 E. Eleven Mile Road WarrenMl48397-5000 United States

The intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that1were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world fonts on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 23 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over SO universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented. © 2016 Society for Imaging Science and Technology.

关键词： Students

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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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Autonomous flight and vision-based target tracking for a flapping-wing MAV

Autonomous flight and vision-based target tracking for a fla...

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IEEE/RSJ International Conference on intelligent robots and Systems

作者： Seungwan Ryu Ukjin Kwon H. Jin Kim Department of Mechanical and Aerospace Engineering Seoul National University Korea Department of Electrical and Computer Engineering Seoul National University Korea

ISBN: (纸本)9781509037636

关键词： Cameras Target tracking Vehicles Streaming media Actuators Data models Batteries

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Research on the Feature Set Construction Method for Spherical Stereo vision 32

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Conference on intelligent robots and computer vision XXXII - algorithms and techniques

作者： Zhu, Junchao Wan, Li Roning, Juha Feng, Weijia Tianjin Univ Technol Tianjin Key Lab Control Theory & Applicat Complic Tianjin Peoples R China Univ Oulu Dept Comp Sci & Engn Oulu Finland Tianjin Normal Univ Coll Comp & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781628414967

Spherical stereo vision is a kind of stereo vision system built by fish-eye lenses, which discussing the stereo algorithms conform to the spherical model. Epipolar geometry is the theory which describes the relationship of the two imaging plane in cameras for the stereo vision system based on perspective projection model. However, the epipolar in uncorrected fish-eye image will not be a line but an arc which intersects at the poles. It is polar curve. In this paper, the theory of nonlinear epipolar geometry will be explored and the method of nonlinear epipolar rectification will be proposed to eliminate the vertical parallax between two fish-eye images. Maximally Stable Extremal Region (MSER) utilizes grayscale as independent variables, and uses the local extremum of the area variation as the testing results. It is demonstrated in literatures that MSER is only depending on the gray variations of images, and not relating with local structural characteristics and resolution of image. Here, MSER will be combined with the nonlinear epipolar rectification method proposed in this paper. The intersection of the rectified epipolar and the corresponding MSER region is determined as the feature set of spherical stereo vision. Experiments show that this study achieved the expected results.

关键词： Spherical stereo vision Epipolar geometry Polar curve MSER

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Particle filter localization and real time obstacle avoidance control based on 3D perception for wheelchair mobile robot

Particle filter localization and real time obstacle avoidanc...

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International IEEE Conference on intelligent Systems, IS

作者： Emna Baklouti Nader Ben Amor Mohamed Jallouli Ecole Nationale d'Ingénieur de Sfax Université de Sfax Tunisie Computer & Embedded Systems Laboratory (CES)

Obstacle detection and localization behaviours have shown to work robustly in 2D perceived environment. With the progress of proximity sensors, precisely the emergence of 3D vision techniques, it would be interesting to examine these motion controllers whether for 3D perceived environment. 2D basic algorithms for obstacle avoidance or robot location, needs reformulation in order to process data from 3D perception devices. In this work, we introduce a 3D obstacle detection controller, combined with particle filter localization. The obstacle detection control described in this paper address 3D obstacles with different shapes and the particle filter uses 3D environment data to correct the wheelchair localization based on his kinematics model.

关键词： Three-dimensional displays Wheelchairs robots Two dimensional displays Kinematics Collision avoidance Sensors

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