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A PROJECT ORIENTED APPROACH TO THE TEACHING OF MACHINE PERCEPTION

IEEE TRANSACTIONS ON EDUCATION 1993年第4期36卷 380-383页

作者： MYLER, HR Department of Electrical and Computer Engineering University of Central Florida Orlando FL USA

Advanced courses in the areas of Machine Perception and Machine Intelligence are not easy to prepare or conduct due to the dynamic research nature of the field. In engineering, our interest is in the construction of intelligent machines in the form of robotic devices or through computer simulation models. Studies in this area are further complicated by the broad range of disciplines that must be accessed in order to provide adequate coverage. This discussion focuses on a set of computer simulation projects that have been assigned at various times during offerings of an advanced graduate level course entitled Machine Perception. The format of the projects are presented with discussion of student results. The projects were novel in that they require advanced techniques of machine vision and are open-ended in that there are no specific solutions. The problems represent the mainstream of machine perception research without requiring more effort than is possible in a one semester course. Students responded with algorithms developed in a variety of computer languages and on various machines.

关键词： Education Humans Machine vision Machine intelligence Signal detection Information processing Layout intelligent robots computer simulation Image analysis

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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...

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

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

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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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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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PYRAMIDAL NEURO-vision ARCHITECTURE FOR vision MACHINES 12

PYRAMIDAL NEURO-VISION ARCHITECTURE FOR VISION MACHINES

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

作者： GUPTA, MM KNOPF, GK UNIV SASKATCHEWAN COLL ENGNINTELLIGENT SYST RES LABSASKATOON S7N 0W0SASKATCHEWANCANADA

ISBN: (纸本)0819413208

The vision system employed by an intelligent robot must be active; active in the sense that it must be capable of selectively acquiring the minimal amount of relevant information for a given task. An efficient active vision system architecture that is based loosely upon the parallel-hierarchical (pyramidal) structure of the biological visual pathway is presented in this paper. Although the computational architecture of the proposed pyramidal neuro-vision system is far less sophisticated than the architecture of the biological visual pathway, it does retain some essential features such as the converging multilayered structure of its biological counterpart. In terms of visual information processing, the neuro-vision system is constructed from a hierarchy of several interactive computational levels, whereupon each level contains one or more nonlinear parallel processors. Computationally efficient vision machines can be developed by utilizing both the parallel and serial information processing techniques within the pyramidal computing architecture. A computer simulation of a pyramidal vision system for active scene surveillance is presented.

关键词： Machine vision Visualization Robot vision Signal processing computer vision technology computer architecture Computing systems Data processing Information visualization Content addressable memory

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AN IMPROVING VISIBILITY METHOD FOR UNDERWATER robots 12

AN IMPROVING VISIBILITY METHOD FOR UNDERWATER ROBOTS

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

作者： LIU, SQ XIA, YX FENGPING, JB WAWG, TL GONG, ZB ACAD SINICA ANHUI INST OPT & FINE MECHHEFEI 230031PEOPLES R CHINA

ISBN: (纸本)0819413208

Fov improving underwater visibility for robots. a method using special intervallic series of light pulses, and two acts of emitting and receiving are performed by two special designed optical shutters and the control signals are synchronized delayed is presented. Calculations show that the received backscattering light can be reduced and so the visible distance increased . This method has several advantages which can make it practical for underwater robots and other actual use. Its feasibility has been demonstrated in the experiments. while only in principle as the limitation of the experimental conditions at present. © 1993 SPIE.

关键词： Underwater visibility

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VERTICES AND CORNERS - A MAXIMUM-LIKELIHOOD APPROACH 12

VERTICES AND CORNERS - A MAXIMUM-LIKELIHOOD APPROACH

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

作者： MALIK, R SO, S STEVENS INST TECHNOL DEPT ELECTR ENGN & COMP SCIHOBOKENNJ 07030

ISBN: (纸本)0819413208

Scenes of polyhedral objects may be accurately represented in 2-D using line sketches. An aim of low level image processing is to generate useful binary images from grey scale images. The binary images generated by enhancement/threshold edge detectors are usually unrefined outlines of the underlying 3-D scene. Such images must be further processed to isolate and identify region boundaries; which, in the case of polyhedra, consist of line segments. The intersection or connection points of these line segments are known as vertices or corners. The work reported in this paper employs a decision theoretic approach to detect vertices in grey scale images.

关键词： Image segmentation computer vision technology Machine vision Robot vision robots Image processing Binary data Silicon 3D image enhancement Sensors

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MORPHOLOGICAL GRANULOMETRIC SHAPE-RECOGNITION IN NOISE 12

MORPHOLOGICAL GRANULOMETRIC SHAPE-RECOGNITION IN NOISE

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

作者： CHENG, YC DOUGHERTY, ER NO TELECOM NETWORK APPLICAT SYSTROCHESTERNY 14609

ISBN: (纸本)0819413208

Shape classification via linear granulometric moments is examined for patterns suffering varying degrees of edge noise. It is seen that recognition is quite poor even for modest amounts of noise and remains poor even when the patterns are first filtered by a close-open filter. Recognition accuracy is greatly improved, for both unfiltered and filtered images, by employing exterior granulometries. These are constructed by applying the various linear structuring-element sequences to the corresponding linear convex hulls of the noisy patterns. The resulting granulometric distributions are then not corrupted by noise-induced probability mass at the left of the pattern spectrum, thereby greatly diminishing the detrimental effects on the pattern spectrum moments.

关键词： Binary data Image processing computer vision technology Machine vision Robot vision robots Image classification Pattern recognition Image filtering Imaging systems

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

GENERAL LEARNING SCHEME FOR ROBOT COORDINATE TRANSFORMATIONS...

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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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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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