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

共 372 条记录，以下是31-40 订阅

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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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intelligent robots and computer vision xxxiII: algorithms and techniques

IS and T International Symposium on Electronic Imaging Scien...

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IS and T International Symposium on Electronic Imaging Science and Technology 2016年

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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

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.

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

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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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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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Improved Obstacle Avoidance and Navigation for an Autonomous Ground Vehicle 32

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

作者： Giri, Binod Cho, Hyunsu Williams, Benjamin C. Tann, Hokchhay Shakya, Bicky Bharam, Vishal Ahlgren, David J. Trinity Coll Hartford CT 06106 USA

ISBN: (纸本)9781628414967

This paper presents improvements made to the intelligence algorithms employed on Q, an autonomous ground vehicle, for the 2014 intelligent Ground Vehicle Competition (IGVC). In 2012, the IGVC committee combined the formerly separate autonomous and navigation challenges into a single AUT-NAV challenge. In this new challenge, the vehicle is required to navigate through a grassy obstacle course and stay within the course boundaries (a lane of two white painted lines) that guide it toward a given GPS waypoint. Once the vehicle reaches this waypoint, it enters an open course where it is required to navigate to another GPS waypoint while avoiding obstacles. After reaching the final waypoint, the vehicle is required to traverse another obstacle course before completing the run. Q uses modular parallel software architecture in which image processing, navigation, and sensor control algorithms run concurrently. A tuned navigation algorithm allows Q to smoothly maneuver through obstacle fields. For the 2014 competition, most revisions occurred in the vision system, which detects white lines and informs the navigation component. Barrel obstacles of various colors presented a new challenge for image processing: the previous color plane extraction algorithm would not suffice. To overcome this difficulty, laser range sensor data were overlaid on visual data. Q also participates in the Joint Architecture for Unmanned Systems (JAUS) challenge at IGVC. For 2014, significant updates were implemented: the JAUS component accepted a greater variety of messages and showed better compliance to the JAUS technical standard. With these improvements, Q secured second place in the JAUS competition.

关键词： Global Positioning System robots Image processing Sensors Navigation systems Cameras computer architecture Control systems Remote sensing Unmanned systems

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The Study of Calibration and Epipolar Geometry for the Stereo vision System Built by Fisheye Lenses 32

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

作者： Zhang, Baofeng Lu, Chunfang Roning, Juha Feng, Weijia Tianjin Univ Technol Tianjin Key Lab Control Theory & Applicat Complic Tianjin Peoples R China Oulu Univ Dept Comp Sci & Engn Oulu Finland Tianjin Normal Univ Coll Comp & Informat Engn Tianjin Peoples R China

ISBN: (纸本)9781628414967

Fish-eye lens is a kind of short focal distance (f=6 similar to 16mm) camera. The field of view (FOV) of it is near or even exceeded 180x180 degrees. A lot of literatures show that the multiple view geometry system built by fish-eye lens will get larger stereo field than traditional stereo vision system which based on a pair of perspective projection images. Since a fish-eye camera usually has a wider-than-hemispherical FOV, the most of image processing approaches based on the pinhole camera model for the conventional stereo vision system are not satisfied to deal with the applications of this category of stereo vision which built by fish-eye lenses. This paper focuses on discussing the calibration and the epipolar rectification method for a novel machine vision system set up by four fish-eye lenses, which is called Special Stereo vision System (SSVS). The characteristic of SSVS is that it can produce 3D coordinate information from the whole global observation space and acquiring no blind area 360 degrees x360 degrees panoramic image simultaneously just using single vision equipment with one time static shooting. Parameters calibration and epipolar rectification is the basic for SSVS to realize 3D reconstruction and panoramic image generation.

关键词： Fish-eye lens Calibration Epipolar rectification

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An Online Visual Loop Closure Detection Method for Indoor Robotic Navigation 32

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

作者： Erhan, Can Sariyanidi, Evangelos Sencan, Onur Temeltas, Hakan Istanbul Tech Univ Control & Automat Engn Dept TR-34469 Istanbul Turkey Ctr Intelligent Sensing London E1 4NS England

ISBN: (纸本)9781628414967

In this paper, we present an enhanced loop closure method* based on image-to-image matching relies on quantized local Zernike moments. In contradistinction to the previous methods, our approach uses additional depth information to extract Zernike moments in local manner. These moments are used to represent holistic shape information inside the image. The moments in complex space that are extracted from both grayscale and depth images are coarsely quantized. In order to find out the similarity between two locations, nearest neighbour (NN) classification algorithm is performed. Exemplary results and the practical implementation case of the method are also given with the data gathered on the testbed using a Kinect. The method is evaluated in three different datasets of different lighting conditions. Additional depth information with the actual image increases the detection rate especially in dark environments. The results are referred as a successful, high-fidelity online method for visual place recognition as well as to close navigation loops, which is a crucial information for the well known simultaneously localization and mapping (SLAM) problem. This technique is also practically applicable because of its low computational complexity, and performing capability in real-time with high loop closing accuracy.

关键词： Loop closure Zernike Moments image processing SLAM depth map indoor navigation

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Automatic restoration of underwater monocular sequences of images

Automatic restoration of underwater monocular sequences of i...

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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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