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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101-110 订阅

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Fast and efficient indexing approach for object recognition

Fast and efficient indexing approach for object recognition

引用

conference on intelligent robots and computer vision XVIII - algorithms, techniques, and Active vision

作者： Hefnawy, A Mashali, S Rashwan, M Fikri, M Elect Res Inst Cairo Egypt

ISBN: (纸本)0819434302

This paper introduces a fast and efficient indexing approach for both 2D & 3D model-based object recognition in the presence of rotation, translation, and scale Variations of objects. The indexing entries are computed after preprocessing the data by Haar wavelet decomposition. The scheme is based on a unified image feature detection approach based on Zernike moments. A set of low level features, e.g. high precision edges, gray level corners, are estimated by a set of orthogonal Zernike moments, calculated locally around every image point. A high dimensional, highly descriptive indexing entries are then calculated based on the correlation of these local features and employed for fast access to the model database to generate hypotheses. A Bst of the most candidate models is then presented by evaluating the hypotheses. Experimental results are included to demonstrate the effectiveness of the proposed indexing approach.

关键词： computer vision multidimensional indexing object recognition wavelet transform

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intelligent robots and computer vision XIV: algorithms, techniques, Active vision, and Materials Handling

Intelligent Robots and Computer Vision XIV: Algorithms, Tech...

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intelligent robots and computer vision XIV: algorithms, techniques, Active vision, and Materials Handling

ISBN: (纸本)0819419524

This conference proceedings contain 70 papers. Topics covered include:Pattern recognition in intelligent robotics;Active vision and control;Color image processing;Systems and applications;Robotic navigation, path planning, and use of motion and image sequences;3D modeling and data processing for robotics and machine vision;Three dimensional pattern recognition for intelligent robots;Neural nets for pattern recognition and machine vision;Feature extraction;and;Detection and segmentation in machine vision.

关键词： computer vision

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Fuzzy logic control for an automated guided vehicle

Fuzzy logic control for an automated guided vehicle

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conference on intelligent robots and computer vision XVII - algorithms, techniques, and Active vision

作者： Cao, M Hall, E Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)081942983X

This paper describes the use of fuzzy logic control for the high level control systems of a mobile robot. The advantages of the fuzzy logic system are that multiple types of input such as that from vision and sonar sensors as well as stored map information can be cased to guide the robot. Sensor fusion can be accomplished between real time sensed information and stored information in a manner similar to a human decision maker. vision guidance is accomplished with a CCD camera with a zoom lens. The data is collected through a commercial tracking device, communicating to the computer the X,Y coordinates of a lane marker. Testing of these systems yielded positive results by showing that at five miles per hour, the vehicle can follow a line and avoid obstacles. The obstacle detection uses information from Polaroid sonar detection system. The motor control system uses a programmable Galil motion control system. This design, in its modularity, creates a portable autonomous controller that could be used for any mobile vehicle with only minor adaptations.

关键词： fuzzy logic vision guidance mobile robots motion control

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Quality classification of wooden surfaces using Gabor filters and genetic feature optimization

Quality classification of wooden surfaces using Gabor filter...

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conference on intelligent robots and computer vision XVIII - algorithms, techniques, and Active vision

作者： Pölzleitner, W Schwingskakl, G Graz Tech Univ A-8010 Graz Austria

ISBN: (纸本)0819434302

We apply a model of texture segmentation using multiple spatially and spectrally localized filters, known as Gabor filters, to the analysis of texture and defect regions found on wooden boards. Specifically we present a method to find an optimal set of parameters for a given two-dimensional object detection method. The method uses banks of Gabor filters to limit the range of spatial frequencies, where mutually distinct textures differ significantly in their dominant characterizing frequencies. By encoding images into multiple narrow spatial frequency and orientation channels a local classification of texture regions can be achieved. Unlike other methods applying Gabor filters, we do not use a full Gabor transform, but use feature selection techniques to maximize discrimination. The selection method uses a genetic algorithm to optimize various parameters of the system including Gabor weights, and the parameters of morphological pre-processing. We demonstrate the applicability of the method to the task of classifying wooden textures, and report experimental results using the proposed method.

关键词： computer vision

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ADAPTATION OF GABOR FILTERS FOR SIMULATION OF HUMAN PREATTENTIVE MECHANISM FOR A MOBILE ROBOT 12

ADAPTATION OF GABOR FILTERS FOR SIMULATION OF HUMAN PREATTEN...

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12th conference on intelligent robots and computer vision: algorithms and techniques

作者： KULKARNI, N NAGHDY, GA UNIV WOLLONGONG DEPT ELECT & COMP ENGNWOLLONGONGNSW 2522AUSTRALIA

ISBN: (纸本)0819413208

vision guided mobile robot navigation is complex and requires analysis of tremendous amounts of information in real time. In order to simplify the task and reduce the amount of information, human preattentive mechanism can be adapted [Nag90]. During the preattentive search the scene is analyzed rapidly but in sufficient detail for the attention to be focused on the `area of interest.' The `area of interest' can further be scrutinized in more detail for recognition purposes. This `area of interest' can be a text message to facilitate navigation. Gabor filters and an automated turning mechanism are used to isolate the `area of interest.' These regions are subsequently processed with optimal spatial resolution for perception tasks. This method has clear advantages over the global operators in that, after an initial search, it scans each region of interest with optimum resolution. This reduces the volume of information for recognition stages and ensures that no region is over or under estimated.

关键词： Image filtering Robot vision robots Machine vision Spatial frequencies Fourier transforms Image segmentation computer vision technology Spatial resolution Visual system

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Creative learning for intelligent robots

Creative learning for intelligent robots

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conference on intelligent robots and computer vision XXV - algorithms, techniques, and Active vision

作者： Liao, Xiaoqun Hall, Ernest L. Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)9780819469243

This paper describes a methodology for creative learning that applies to man and machines. Creative learning is a general approach used to solve optimal control problems. The creative controller for intelligent machines integrates a dynamic database and a task control center into the adaptive critic learning model. The task control center can function as a command center to decompose tasks into sub-tasks with different dynamic models and criteria functions, while the dynamic database can act as an information system. To illustrate the theory of creative control, several experimental simulations for robot arm manipulators and mobile wheeled vehicles were included. The simulation results showed that the best performance was obtained by using adaptive critic controller among all other controllers. By changing the paths of the robot arm manipulator in the simulation, it was demonstrated that the learning component of the creative controller was adapted to a new set of criteria. The Bearcat Cub robot was another experimental example used for testing the creative control learning. The significance of this research is to generalize the adaptive control theory in a direction toward highest level of human learning - imagination. In doing this it is hoped to better understand the adaptive learning theory and move forward to develop more human-intelligence-like components and capabilities into the intelligent robot. It is also hoped that a greater understanding of machine learning will motivate similar studies to improve human learning.

关键词： adaptive critic design dynamic programming creative learning Neurocontrol intelligent robots artificial intelligence

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Obstacle avoidance system with sonar sensing and fuzzy logic

Obstacle avoidance system with sonar sensing and fuzzy logic

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conference on intelligent robots and computer vision XVI - algorithms, techniques, Active vision, and Materials Handling

作者： Chiang, WC Kelkar, N Hall, EL Univ. of Cincinnati (United States)

ISBN: (纸本)0819426407

Automated Guided Vehicles (AGV's) have many potential applications in manufacturing, medicine, space and defense. The purpose of this paper is to describe exploratory research on the design of an obstacle avoidance system using sonar sensors for a modular autonomous mobile robot controller. The advantages of a modular system are related to portability and the fact that any vehicle can become autonomous with minimal modifications. A mobile robot test-bed has been constructed using a golf cart base. The obstacle avoidance system is based on a micro-controller interfaced with multiple ultrasonic transducers. This micro-controller independently handles all timing and distance calculations and sends a distance measurement back to the computer via the serial line. This design yields a portable independent system. Testing of these systems has been done in the lab as well as on an outside test track with positive results that show that at five mph the vehicle can follow a line and at the same time avoid obstacles. This design, in its modularity, creates a portable autonomous obstacle avoidance controller applicable for any mobile vehicle with only minor adaptations.

关键词： sonar sensing fuzzy logic obstacle avoidance and mobile robots

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Optimizing a Mobile Robot Control System using GPU Acceleration

Optimizing a Mobile Robot Control System using GPU Accelerat...

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

作者： Tuck, Nat McGuinness, Michael Martin, Fred Univ Massachusetts Lowell Lowell MA 01854 USA

ISBN: (纸本)9780819489487

This paper describes our attempt to optimize a robot control program for the intelligent Ground Vehicle Competition (IGVC) by running computationally intensive portions of the system on a commodity graphics processing unit (GPU). The IGVC Autonomous Challenge requires a control program that performs a number of different computationally intensive tasks ranging from computer vision to path planning. For the 2011 competition our Robot Operating System (ROS) based control system would not run comfortably on the multicore CPU on our custom robot platform. The process of profiling the ROS control program and selecting appropriate modules for porting to run on a GPU is described. A GPU-targeting compiler, Bacon, is used to speed up development and help optimize the ported modules. The impact of the ported modules on overall performance is discussed. We conclude that GPU optimization can free a significant amount of CPU resources with minimal effort for expensive user-written code, but that replacing heavily-optimized library functions is more difficult, and a much less efficient use of time.

关键词： robotics stereo vision GPU acceleration

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The 18TH Annual intelligent Ground Vehicle Competition: Trends and Influences for intelligent Ground Vehicle Control

The 18TH Annual Intelligent Ground Vehicle Competition: Tren...

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conference on intelligent robots and computer vision XXVIII: algorithms and techniques

作者： Theisen, Bernard L. Frederick, Philip Smuda, William USA TARDEC Warren MI 48397 USA

ISBN: (纸本)9780819484154

The intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were 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 focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 18 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 75 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.

关键词： intelligent robots autonomous systems ground vehicles vehicle control engineering education IGVC

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A Multiple Feature Based Particle Filter Using Mutual Information Maximization

A Multiple Feature Based Particle Filter Using Mutual Inform...

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conference on intelligent robots and computer vision XXVIII: algorithms and techniques

作者： Hong, Kihyun Han, Kyuseo Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9780819484154

In designing a tracking algorithm, utilizing several different features, e. g., color histogram, gradient histogram and other object descriptors, is preferable to increase robustness of tracking performance. In this paper, we propose a multiple feature fusion framework to improve the tracking by assigning appropriate weights to individual features. The feature weights are optimally obtained by a waterfilling procedure that maximizes mutual information between target object features and query features. Especially, in this paper, we focus on a particle filter tracking implementation of the multiple feature fusion framework. Our experiments show that object tracking with multiple features outperforms single feature based tracking methods and illustrates that the proposed optimal feature weighting increases robustness of multiple-feature based tracking performance.

关键词： Particle filters Detection and tracking algorithms Particles Process modeling Algorithm development Signal to noise ratio Visual process modeling computer vision technology Dynamical systems Machine vision

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