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检索条件"任意字段=27th Conference on Intelligent Robots and Computer Vision: Algorithms and Techniques"

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LINE GROUPING USING PERCEPTUAL SALIENCY AND STRUCTURE PREDICTION FOR CAR DETECTION IN TRAFFIC SCENES 12

LINE GROUPING USING PERCEPTUAL SALIENCY AND STRUCTURE PREDIC...

引用

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

作者： DENASI, S QUAGLIA, G IST ELETTROTECNICO NAZL GALILEO FERRARIS I-10135 TURINITALY

ISBN: (纸本)0819413208

Autonomous and guide assisted vehicles make a heavy use of computer vision techniques to perceive the environment where they move. In this context, the European PROMEthEUS program is carrying on activities in order to develop autonomous vehicle monitoring that assists people to achieve safer driving. Car detection is one of the topics that are faced by the program. Our contribution proposes the development of this task in two stages: the localization of areas of interest and the formulation of object hypotheses. In particular, the present paper proposes a new approach that builds structural descriptions of objects from edge segmentations by using geometrical organization. this approach has been applied to the detection of cars in traffic scenes. We have analyzed images taken from a moving vehicle in order to formulate obstacle hypotheses: preliminary results confirm the efficiency of the method.

关键词： Image segmentation Roads computer vision technology Machine vision Robot vision robots Image processing Computing systems Visual system Visual process modeling

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GENERAL LEARNING SCHEME FOR ROBOT COORDINATE TRANSFORMATIONS USING DYNAMIC NEURAL-NETWORK 12

GENERAL LEARNING SCHEME FOR ROBOT COORDINATE TRANSFORMATIONS...

引用

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

作者： GUPTA, MM RAO, DH UNIV SASKATCHEWAN COLL ENGNINTELLIGENT SYST RES LABSASKATOON S7N 0W0SASKATCHEWANCANADA

ISBN: (纸本)0819413208

By virtue of their functional approximation, learning and adaptive capabilities, the computational neural networks can be suitably employed for learning robot coordinate transformations. the major drawback of conventional static feedforward neural networks based on back-propagation learning algorithm is in their very large convergence time for a given task. Any attempts to accelerate the learning process by increasing the values of learning constants in the algorithm often result in unstable systems. the intent of this paper is to describe a neural network structure called dynamic neural processor (DNP), and examine briefly how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. the architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. computer simulations are provided to demonstrate the effectiveness of the proposed learning scheme using the DNP.

关键词： Neurons Neural networks Robot vision Kinematics computer vision technology Machine vision Algorithm development Evolutionary algorithms Robotics computer simulations

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VERTICES AND CORNERS - NORMALIZED AVERAGE DETECTION 12

VERTICES AND CORNERS - NORMALIZED AVERAGE DETECTION

引用

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

作者： MALIK, R REN, H STEVENS INST TECHNOL DEPT ELECT ENGN & COMP SCIHOBOKENNJ 07030

ISBN: (纸本)0819413208

Most of the information regarding the shape of polyhedral objects is preserved in the edges and the vertices of these objects. Gray level images of scenes containing such objects are often processed to extract edge and vertex information to produce equivalent line sketches. An accurate line sketch of a scene serves as an effective input to high level vision systems concerned with scene understanding or object recognition. the performance of these systems is therefore greatly dependent on the accuracy of the line sketch. the work reported in this paper addresses the issues associated with generating accurate line sketches from gray level images. the methods described here have been implemented and tested with real and synthetic images and are compared to other vertex or corner detection techniques. the performance of the vertex detector is assessed using simulation runs on images with varied signal-to-noise ratios. the computational performance of this algorithm is evaluated and assessed by operating directly on the gray-scale image.

关键词： computer vision technology Machine vision Robot vision robots Image segmentation Edge detection Corner detection Signal to noise ratio Image processing Feature extraction

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the 12^th annual intelligent ground vehicle competition:: Team approaches to intelligent vehicles

The 12<SUP>TH</SUP> annual intelligent ground vehicle compet...

引用

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

作者： theisen, BL Maslach, D USA Tank Automat Res Dev & Engn Ctr Warren MI 48397 USA

ISBN: (纸本)081945561X

the intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. 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. Both U.S. and international teams focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 12 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 43 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 three-day competition are highlighted. Finally, an assessment of the competition based on participant feedback is presented.

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

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vision-BASED ORIENTATION AND POSITION DETECTION OF ICS AND PCBS 12

VISION-BASED ORIENTATION AND POSITION DETECTION OF ICS AND P...

引用

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

作者： CHUNG, HK PARK, RH SOGANG UNIV DEPT ELECTR ENGNSEOUL 100611SOUTH KOREA

ISBN: (纸本)0819413208

In this paper, a high-resolution algorithm for detecting the orientation and position of an IC, and an algorithm for compensating the position and skew angle of a PCB, are proposed. the proposed algorithm for the first topic consists of two parts. Its first part is a preprocessing step, in which corner points of an IC are detected and are separated into two groups. then the coarse angle of the principal axis is obtained by line fitting. the second part is a main processing step, in which the Hough transform over the limited range of angles is applied to the corner points to detect precisely the orientation of an IC or a surface mounting device (SMD). the position of an IC or SMD is determined by using its four corner points. the proposed algorithm for the second topic is the one which detects a rotation angle and translation parameters of a PCB using a template matching method. the PCB is compensated by the detected parameters. the computer simulation shows that the parameters obtained by proposed algorithms are more accurate than those by the several conventional methods considered. the proposed algorithms can be applied to the fast and accurate automatic inspection systems.

关键词： Hough transforms robots Robot vision computer vision technology Machine vision Detection and tracking algorithms Corner detection Inspection Information operations Lead

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BEYOND PURE STATIC SHAPE IN FUNCTION-BASED OBJECT RECOGNITION 12

BEYOND PURE STATIC SHAPE IN FUNCTION-BASED OBJECT RECOGNITIO...

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

作者： BOWYER, KW STARK, L UNIV S FLORIDA TAMPAFL 33620

ISBN: (纸本)0819413208

there has recently been growing interest in exploiting the concept of reasoning about function for object recognition. In a function-based approach to object recognition, recognition of an object means labeling it as belonging to some category of objects according to the function that it could serve. the few function-based recognition systems which have so far been described in the literature have all assumed that the input to the problem is a pure static shape description. By `pure' shape we mean that the only object property that the systems have reasoned about is their abstract shape. By `static' shape we mean that the systems have reasoned about an object from only a single (assumed rigid) abstract shape instance. this paper discusses some of the issues which must be addressed in extending the function-based approach to handle non-shape properties (such as material properties) and dynamic shape descriptions.

关键词： computer vision technology Machine vision Object recognition 3D modeling Visual process modeling Robot vision robots Aluminum Computing systems Shape analysis

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GENERAL VISUAL ROBOT CONTROLLER NETWORKS VIA ARTIFICIAL EVOLUTION 12

GENERAL VISUAL ROBOT CONTROLLER NETWORKS VIA ARTIFICIAL EVOL...

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

作者： CLIFF, D HARVEY, I HUSBANDS, P UNIV SUSSEX SCH COGNIT & COMP SCIBRIGHTON BN1 9QHE SUSSEXENGLAND

ISBN: (纸本)0819413208

We discuss recent results from our ongoing research concerning the application of artificial evolution techniques (i.e., an extended form of genetic algorithm) to the problem of developing `neural' network controllers for visually guided robots. the robot is a small autonomous vehicle with extremely low-resolution vision, employing visual sensors which could readily be constructed from discrete analog components. In addition to visual sensing, the robot is equipped with a small number of mechanical tactile sensors. Activity from the sensors is fed to a recurrent dynamical artificial `neural' network, which acts as the robot controller, providing signals to motors governing the robot's motion. Prior to presentation of new results, this paper summarizes our rationale and past work, which has demonstrated that visually guided control networks can arise without any explicit specification that visual processing should be employed: the evolutionary process opportunistically makes use of visual information if it is available.

关键词： Visualization Sensors Chlorine Robot vision Genetic algorithms Device simulation Neural networks computer vision technology Machine vision Network architectures

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DESIGN AND IMPLEMENTATION OF A FUZZY-LOGIC YAW CONTROLLER 12

DESIGN AND IMPLEMENTATION OF A FUZZY-LOGIC YAW CONTROLLER

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

作者： WU, KC SWIFT, AHP CRAVER, WL CHANG, YC UNIV TEXAS DEPT MECH & IND ENGNEL PASOTX 79968

ISBN: (纸本)0819413208

this paper describes a fuzzy logic controller (FLC) designed and implemented to control the yaw angle of a 10 kW fixed speed teetered-rotor wind turbine presently being commissioned at the University of Texas at El Paso. the technical challenge of this project is that the wind turbine represents a highly stochastic nonlinear system. the problems associated with the wind turbine yaw control are of a similar nature as those experienced with position control of high inertia equipment like tracking antenna, gun turrets, and overhead cranes. Furthermore, the wind turbine yaw controller must be extremely cost-effective and highly reliable in order to be economically viable compared to the fossil fueled power generators.

关键词： Fuzzy logic Wind turbine technology Control systems Fuzzy systems robots computer vision technology Electroluminescence Machine vision Robot vision Complex systems

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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...

引用

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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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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