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

共 670 条记录，以下是141-150 订阅

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Modeling of radial asymmetry in lens distortion facilitated by modern optimization techniques

Modeling of radial asymmetry in lens distortion facilitated ...

引用

27th Conference on intelligent robots and computer vision: algorithms and techniques

作者： de Villiers, Jason P. Leuschner, F. Wilhelm Geldenhuys, Ronelle CSIR Meiring Naude Rd Pretoria South Africa Univ Pretoria Dept Elect Elect & Comp Engn Pretoria South Africa

ISBN: (纸本)9780819479327

Most current lens distortion models use only a few terms of Brown's model, which assumes that the radial distortion is dependant only on the distance from the distortion centre, and an additive tangential distortion can be used to correct lens de-centering. This paper shows that the characterization of lens distortion can be improved by over 79% compared to prevailing methods. This is achieved by using modern numerical optimization techniques such as the Leapfrog algorithm, and sensitivity-normalized parameter scaling to reliably and repeatably determine more terms for Brown's model. An additional novel feature introduced in this paper is to allow the distortion to vary not only with polar distance but with the angle too. Two models for radially asymmetrical distortion (i.e. distortion that is dependant on both polar angle and distance) are discussed, implemented and contrasted to results obtained when no asymmetry is modelled. A sample of 32 cameras exhibiting extreme barrel distortion (due to their 6.0mm focal lengths) is used to show that these new techniques can straighten lines to within 7 hundredths of a pixel RMS over the entire image.

关键词： Asymmetry numerical optimization distortion characterization real-time

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LandingNav: A precision autonomous landing sensor for robotic platforms on planetary bodies

LandingNav: A precision autonomous landing sensor for roboti...

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27th Conference on intelligent robots and computer vision: algorithms and techniques

作者： Katake, Anup Bruccoleri, Christian Singla, Puneet Junkins, John L. StarVis Technol Inc 400 Harvey Mitchell Pkwy SSuite 400 College Stn TX 77845 USA Univ Buffalo Dept Mech & Aerosp Engn Buffalo NY USA Texas A&M Univ Dept Aerosp Engn College Stn TX 77843 USA

ISBN: (纸本)9780819479327

Increased interest in the exploration of extra terrestrial planetary bodies calls for an increase in the number of spacecraft landing on remote planetary surfaces. Currently, imaging and radar based surveys are used to determine regions of interest and a safe landing zone. The purpose of this paper is to introduce LandingNav, a sensor system solution for autonomous landing on planetary bodies that enables landing on unknown terrain. LandingNav is based on a novel multiple field of view imaging system that leverages the integration of different state of the art technologies for feature detection, tracking, and 3D dense stereo map creation. In this paper we present the test flight results of the LandingNav system prototype. Sources of errors due to hardware limitations and processing algorithms were identified and will be discussed. This paper also shows that addressing the issues identified during the post-flight test data analysis will reduce the error down to 1-2%, thus providing for a high precision 3D range map sensor system.

关键词： autonomous planetary landing stereo vision terrain mapping dense range map estimation localization

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Color Image Processing for Date Quality Evaluation

Color Image Processing for Date Quality Evaluation

引用

27th Conference on intelligent robots and computer vision: algorithms and techniques

作者： Lee, Dah-Jye Archibald, James K. Brigham Young Univ Provo UT 84602 USA

ISBN: (纸本)9780819479327

Many agricultural non-contact visual inspection applications use color image processing techniques because color is often a good indicator of product quality. Color evaluation is an essential step in the processing and inventory control of fruits and vegetables that directly affects profitability. Most color spaces such as RGB and HSV represent colors with three-dimensional data, which makes using color image processing a challenging task. Since most agricultural applications only require analysis on a predefined set or range of colors, mapping these relevant colors to a small number of indexes allows simple and efficient color image processing for quality evaluation. This paper presents a simple but efficient color mapping and image processing technique that is designed specifically for real-time quality evaluation of Medjool dates. In contrast with more complex color image processing techniques, the proposed color mapping method makes it easy for a human operator to specify and adjust color-preference settings for different color groups representing distinct quality levels. Using this color mapping technique, the color image is first converted to a color map that has one color index represents a color value for each pixel. Fruit maturity level is evaluated based on these color indices. A skin lamination threshold is then determined based on the fruit surface characteristics. This adaptive threshold is used to detect delaminated fruit skin and hence determine the fruit quality. The performance of this robust color grading technique has been used for real-time Medjool date grading.

关键词： machine vision color mapping color grading Medjool date non-contact visual inspection

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On-Line Measurement of Ski-Jumper trajectory: combining Stereo vision and Shape Description

On-Line Measurement of Ski-Jumper trajectory: combining Ster...

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27th Conference on intelligent robots and computer vision: algorithms and techniques

作者： Nunner, T. Sidla, O. Paar, G. Nauschnegg, B. Joanneum Res Inst Digital Image Proc Wastiangasse 6 A-8010 Graz Austria SLR Engn EU A-8010 Graz Austria

ISBN: (纸本)9780819479327

Ski jumping has continuously raised major public interest since the early 70s of the last century, mainly in Europe and Japan. The sport undergoes high-level analysis and development, among others, based on biodynamic measurements during the take-off and flight phase of the jumper. We report on a vision-based solution for such measurements that provides a full 3D trajectory of unique points on the jumper's shape. During the jump synchronized stereo images are taken by a calibrated camera system in video rate. Using methods stemming from video surveillance, the jumper is detected and localized in the individual stereo images, and learning-based deformable shape analysis identifies the jumper's silhouette. The 3D reconstruction of the trajectory takes place on standard stereo forward intersection of distinct shape points, such as helmet top or heel. In the reported study, the measurements are being verified by an independent GPS measurement mounted on top of the Jumper's helmet, synchronized to the timing of camera exposures. Preliminary estimations report an accuracy of +/-20 cm in 30 Hz imaging frequency within 40m trajectory. The system is ready for fully-automatic on-line application on ski-jumping sites that allow stereo camera views with an approximate base-distance ratio of 1: 3 within the entire area of investigation.

关键词： ski-jumping active-shape-model calibration stereo-reconstruction online-tracking Eigenshape GPS

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Comparison of Three Control Methods for an Autonomous Vehicle

Comparison of Three Control Methods for an Autonomous Vehicl...

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27th Conference on intelligent robots and computer vision: algorithms and techniques

作者： Deshpande, Anup Mathur, Kovid Hall, Ernest Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)9780819479327

The desirability and challenge of developing a completely autonomous vehicle and the rising need for more efficient use of energy by automobiles motivate the search for an optimum solution to computer control of energy efficient vehicles. The purpose of this paper is to compare three control methods - mechanical, hydraulic and electric that have been used to convert an experimental all terrain vehicle to drive by wire which would eventually act as a test bed for conducting research on various technologies for autonomous operation. computer control of basic operations in a vehicle namely steering, braking and speed control have been implemented and will be described in this paper. The output from a 3 axis motion controller is used for this purpose. The motion controller is interfaced with a software program and WSDK (Windows Servo Design Kit) serves as an intermediate tuning layer for tuning and parameter settings in autonomous operation. The software program is developed in C++ and the voltage signal sent to the motion controller can be varied through the control program for desired results in controlling the steering motor, activating the hydraulic brakes and varying the vehicle's speed. The vehicle has been tested for its basic functionality which includes testing of street legal operations and also a 1000 mile test while running in a hybrid mode. The vehicle has also been tested for control when it is interfaced with devices such as a keyboard, joystick and sensors under full autonomous operation. The vehicle is currently being tested in various safety studies and is being used as a test bed for experiments in control courses and research studies. The significance of this research is in providing a greater understanding of conventional driving controls and the possibility of improving automobile safety skills.

关键词： intelligent autonomous vehicle electrical control hydraulic control mechanical control human interface

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Handling of Split-and-Merge Effects and Occlusions using Feature-Based Probabilistic Data Association

Handling of Split-and-Merge Effects and Occlusions using Fea...

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27th Conference on intelligent robots and computer vision: algorithms and techniques

作者： Grinberg, Michael Ohr, Florian Fraunhofer Inst Informat & Data Proc IITB D-761313 Karlsruhe Germany

ISBN: (纸本)9780819479327

One of the big challenges in multi-target tracking is the track management and correct data association between measurements and tracks. Major reason for tracking errors are detection failures such as merged, split, incomplete or missed detections as well as clutter-based detections ( phantom objects). Those effects combined with uncertainties in existence and number of objects in the scene as well as uncertainties in their observability and dynamic object state lead to gross tracking errors. In this contribution we present an algorithm for visual detection and tracking of multiple extended targets which is capable of coping with occlusions and split and merge effects. Unlike most of the state-of-the-art approaches we utilize information about the measurements' composition gained through tracking dedicated feature points in the image and in 3D space, which allows us to reconstruct the desired object characteristics from the data even in the case of detection errors due to above-mentioned reasons. The proposed Feature-Based Probabilistic Data Association approach resolves data association ambiguities in a soft threshold-free decision based not only on target state prediction but also on the existence and observability estimation modeled as two additional Markov chains. A novel measurement reconstruction scheme allows for a correct innovation in case of split, merged and incomplete measurements realizing thus a detection-by-tracking approach. This process is assisted by a grid based object representation which offers a lower abstraction level of targets extent and is used for detailed occlusion analysis.

关键词： multitarget tracking 9MTT) feature-based tracking track-before-detect detection-by-tracking probabilistic data association point tracking 6D-vision split and merge handling occlusion handling stereo video environment perception

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vision-based lane detection for an autonomous ground vehicle: A comparative field test

Vision-based lane detection for an autonomous ground vehicle...

引用

Southeastern Symposium on System Theory

作者： Forrest N. Bush Joel M. Esposito US Naval Academy Annapolis MD USA

ISBN: (纸本)9781424456901

We examine the problem of designing computer vision algorithms to autonomously drive an off road vehicle between two lane markings painted on the ground. In this paper we describe field tests used to compare the efficacy of two popular line extractions techniques from the literature: the Hough Transform and the RANSAC Algorithm. Although it is very implementation dependent, we found the Hough Transform to be superior to the RANSAC algorithm in both speed and accuracy for identifying lane markings in the off road environment.

关键词： Vehicle detection Land vehicles Testing Road vehicles Remotely operated vehicles computer vision Mobile robots Global Positioning System Road transportation intelligent vehicles

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Proceedings of SPIE-IS and T Electronic Imaging - intelligent robots and computer vision XXVI: algorithms and techniques

Proceedings of SPIE-IS and T Electronic Imaging - Intelligen...

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intelligent robots and computer vision XXVI: algorithms and techniques

The proceedings contain 28 papers. The topics discussed include: geometric alignment method for large point cloud pairs using sparse overlap areas;a probabilistic approach for the reconstruction of polyhedral objects using shape from shading technique;people detection in crowded scenes using active contour models;homography-based multiple-camera person-tracking;hybrid real-time tracking of non-rigid objects under occlusions;combining a modified vector field histogram algorithm and real-time image processing for unknown environment navigation;development of a vision system for an intelligent ground vehicle;construction engineering robot kit: warfighter experiment;convoy active safety technologies warfighter experiment II;locating and tracking objects by efficient comparison of real and predicted synthetic video imagery;and scene categorization with multi-scale category-specific visual words.

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Real Time Object Recognition Methodology

Real Time Object Recognition Methodology

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Electronics, Robotics and Automotive Mechanics Conference

作者： M. Peña Cabrera I. López Juárez R. Ríos Cabrera R. Osorio H. Gómez UNAM Mexico Mexico Institute of Research of Applied Mathematics and Systems (IIMAS-UNAM) México CINVESTAV Saltillo México

This paper shows a methodology for on-line recognition and classification of pieces in robotic assembly tasks and its application into an intelligent manufacturing cell. The performance of industrial robots working in unstructured environments can be improved using visual perception and learning techniques The object recognition is accomplished using a neuronal network with FuzzyARTMAP architecture for learning and recognition purposes, which receives a descriptor vector called CFD&POSE as the input. This vector represents an innovative methodology for classification and identification of pieces in robotic tasks, every single stage of the methodology, is described step by step and the proposed algorithms explained. The vector compresses 3D object data from assembly parts and is invariant to scale, rotation and orientation. The approach in combination with the fast learning capability of ART networks indicates the suitability for industrial robot applications as it is shown in experimental results and the possibility to add concatenated information into the descriptor vector to achieve a much more robust methodology.

关键词： Robot sensing systems Assembly computer architecture Machine vision Pixel Artificial neural networks

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Architectures for intelligent robots in the age of exploitation

Architectures for intelligent robots in the age of exploitat...

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intelligent robots and computer vision XXVI: algorithms and techniques

作者： Hall, E.L. Ali, S.M. Alhaj Ghaffari, M. Liao, X. Sarkar, Saurabh Mathur, Kovid Tennety, Srinivas Center for Robotics Research University of Cincinnati Cincinnati OH 45221-0072 United States Hashemite Univ. Jordan

History shows that problems that cause human confusion often lead to inventions to solve the problems, which then leads to exploitation of the invention, creating a confusion-invention-exploitation cycle. Robotics, which started as a new type of universal machine implemented with a computer controlled mechanism in the 1960's, has progressed from an Age of Over-expectation, a Time of Nightmare, an Age of Realism, and is now entering the Age of Exploitation. The purpose of this paper is to propose architecture for the modern intelligent robot in which sensors permit adaptation to changes in the environment are combined with a "creative controller" that permits adaptive critic, neural network learning, and a dynamic database that permits task selection and criteria adjustment. This ideal model may be compared to various controllers that have been implemented using Ethernet, CAN Bus and JAUS architectures and to modern, embedded, mobile computing architectures. Several prototypes and simulations are considered in view of peta-computing. The significance of this comparison is that it provides some insights that may be useful in designing future robots for various manufacturing, medical, and defense applications. © 2009 SPIE-IS&T.

关键词： Reinforcement learning

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