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Proceedings of SPIE - The International Society for Optical Engineering 1996年 2904卷 361-369页

作者： Xu, Zhanping Schwarte, Rudolf Heinol, Horst G. Lange, Robert Li, J. Univ. Siegen Siegen Ger

ISBN: (纸本)0819423068;9780819423061

This paper focuses on simulating a model of 3D-color vision system based on synthetic nonlinear modulation. The model is set up to recover 3D and color properties from a colored object through evaluating several rf-interferograms sampled by a black-white CCD camera. Colorizing a black-white CCD camera in a 3D-vision system implies high resolution. The synthetic nonlinear modulation is different from other 3D-color vision systems. Different colored lights are synchronously modulated with characterizing rf-frequencies to detect a 3D object. Recovering colors is equally treated as recovering 3D information. Optical filters are not used. Instead, a suitable algorithm is adopted for recovering color and 3D information. Since a modulated optical rf-signal is used as a detecting probe rather than an unmodulated optical wave, higher orders of harmonic signals may be caused by electrical or optical components. Although linear matching techniques are adapted to prevent the problem, it is necessary to simulate the vision system for predicting its performances. An 8-bit black-white CCD camera with different signal to noise ratios is taken as an example in the simulation. 3D color properties are evaluated for the system in the case of nonlinearity and noise. An optimized result is obtained for realizing this vision system.

关键词： computer vision

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Neural network system for purposeful behavior based on foveal visual preprocessor

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 1996年 2904卷 256-262页

作者： Golovan, Alexander V. Shevtsova, Natalia A. Klepatch, Arkadi A. Rostov State Univ. Rostov-on-Don Russia

ISBN: (纸本)0819423068;9780819423061

Biologically plausible model of the system with an adaptive behavior in a priori environment and resistant to impairment has been developed. The system consists of input, learning, and output subsystems. The first subsystems classifies input patterns presented as n-dimensional vectors in accordance with some associative rule. The second one being a neural network determines adaptive responses of the system to input patterns. Arranged neural groups coding possible input patterns and appropriate output responses are formed during learning by means of negative reinforcement. Output subsystem maps a neural network activity into the system behavior in the environment. The system developed has been studied by computer simulation imitating a collision-free motion of a mobile robot. After some learning period the system 'moves' along a road without collisions. It is shown that in spite of impairment of some neural network elements the system functions reliably after relearning. Foveal visual preprocessor model developed earlier has been tested to form a kind of visual input to the system.

关键词： computer vision

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Feature spacing trajectory representation and processing for active vision

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 1996年 2904卷 390-401页

作者： Casasent, David P. Sipe, Michael Carnegie Mellon Univ. Pittsburgh PA USA

ISBN: (纸本)0819423068;9780819423061

A new feature space trajectory (FST) description of 3D distorted views of an object is advanced for active vision applications. In an FST, different distorted object views are vertices in feature space. A new eigen-feature space and Fourier transform features are used. Vertices for different adjacent distorted views are connected by straight lines so that an FST is created as the viewpoint changes. Each different object is represented by a distinct FST. An object to be recognized is represented as a point in feature space; the closest FST denotes the class of the object, and the closest line segment on the FST indicates its pose. A new neural network is used to efficiently calculate distances. We discuss its uses in active vision. Apart from an initial estimate of object class and pose, the FST processor can specify where to move the sensor to: confirm class and pose, to grasp the object, or to focus on a specific object part for assembly or inspection. We advance initial remarks on the number of aspect views needed and which aspect views are needed to represent an object. We note the superiority of our eigenspace for discrimination, how it can provide shift invariance, and how the FST overcomes problems associated with other classifiers.

关键词： computer vision

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Active vision and adaptive learning

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 1996年 2904卷 413-424页

作者： Peters, Mark Sowmya, Arcot Univ. of New South Wales Sydney Aust

ISBN: (纸本)0819423068;9780819423061

Active vision is identified by a closed loop linking sensing with acting. Thus, an active vision system's behavior is directly determined by what it senses. To date however, the responses produced by active vision systems have tended to be relatively low-level, generally designed to facilitate improved sensing, by enhancing the duration or speed of object tracking, for example, or optimizing the focused application of more intensive image processing. This is probably adequate if the active vision system is designed as a front end to other processes or to specialized application systems, or if it is a demonstration in support of a theoretical vision model. However, this leaves unanswered the problems of i) how to select an appropriate action when many different alternatives are available, and ii) how best to modify the behavioral repertoire of the system. These problems are especially important in two situations: firstly, when an autonomous system faces a novel situation and must respond adaptively without the benefit of a priori knowledge, and secondly, when systems attempt higher levels of perception and response, and links between the absolute properties of the incoming image data and the actual objects of perception become increasingly attenuated. This paper discusses methods for linking learning with active vision so that the behavior of the system is optimized over time for the achievement of goals. We argue the necessity of system goals in learning vision systems, and discuss methods for propagating goals through all levels of loose hierarchies. In the last section we outline an architecture in which high and low level perception operate interactively and in parallel.

关键词： computer vision

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Cavity surface measuring system using stereo reconstruction

Cavity surface measuring system using stereo reconstruction

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Conference on intelligent robots and computer vision XV: algorithms, techniques, Active vision, and Materials Handling

作者： Paar, G Bauer, A Joanneum Research Institute (Austria)

ISBN: (纸本)0819423068

Three-dimensional (3D) reconstruction of highly textured surfaces on unvegetated (rock-like) terrain is of major interest for stereo vision based mapping applications. We describe a prototype system for automatic modeling of such scenes. It is based on two frame CCD cameras, which are tightly attached to each other ensuring constant relative orientation. One camera is used to acquire known reference points to get the exterior orientation of the system, the other records the surface images. The system is portable to keep image acquisition as short as possible. Automatic calibration using the images acquired by the calibration camera permits the computation of exterior orientation parameters of the surface camera via a transformation matrix. A robust matching method providing dense disparities together with a flexible reconstruction algorithm renders an accurate grid of 3D points on arbitrarily shaped surfaces. The results of several stereo reconstructions are merged. Projection onto the global shape allows easy evaluation of volumes, and thematic mapping with respect to the desired surface geometry in construction processes. We report on accuracy and emphasize on the practical usage. It is shown that the prototype system is able to generate a proper data set of surface descriptions that is accurate and dense enough to serve as documentation, planning and accounting basis.

关键词： stereo matching 3D reconstruction computer vision photogrammetry calibration rock surface volume measurements

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Active vision and adaptive learning

Active vision and adaptive learning

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Conference on intelligent robots and computer vision XV: algorithms, techniques, Active vision, and Materials Handling

作者： Peters, M Sowmya, A Univ. of New South Wales (Australia)

ISBN: (纸本)0819423068

Active vision is identified by a closed loop linking sensing with acting. Thus, an active vision system's behaviour is directly determined by what it senses. To date however, the responses produced by active vision systems have tended to be relatively low-level, generally designed to facilitate improved sensing, by enhancing the duration or speed of object tracking, for example, or optimising the focussed application of more intensive image processing. This is probably adequate if the active vision system is designed as a front end to other processes or to specialised application systems, or if it is a demonstration in support of a theoretical vision model. However, this leaves unanswered the problems of i) how to select an appropriate action when many different alternatives are available, and ii) how best to modify the behavioural repertoire of the system. These problems are especially important in two situations: firstly, when an autonomous system faces a novel situation and must respond adaptively without the benefit of a priori knowledge, and secondly, when systems attempt higher levels of perception and response, and links between the absolute properties of the incoming image data and the actual objects of perception become increasingly attenuated. This paper discusses methods for linking learning with active vision so that the behaviour of the system is optimised over time for the achievement of goals. We argue the necessity of system goals in learning vision systems, and discuss methods for propagating goals through all levels of loose hierarchies. In the last section we outline an architecture in which high and low level perception operate interactively and in parallel.

关键词： active vision adaptive learning motion tracking object tracking human movement foveating saccades

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Feature tracking from an image sequence using affine invariance and Hough transform

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 1996年 2904卷 493-504页

作者： Tsui, H.T. Kong, S.K. Chan, C.W. Chinese Univ. of Hong Kong Shatin N T Hong Kong

ISBN: (纸本)0819423068;9780819423061

Feature point tracking from an image sequence is an important step in many methods of image understanding including shape from motion and mobile robot navigation. Assuming an affine camera model, this paper proposed a new tracking method using affine invariance. Any 3D feature point can have unique coordinates with reference to an affine basis and the affine coordinates are invariant to affine transformation: camera rotations and translations. The images of a set of 4 control points defining an affine basis are tracked in an image sequence using a conventional method. Under this assumption, given a feature point in any image, its locus in the first image is a straight line. The straight lines of the corresponding features from the image sequence will intersect at a point, the corresponding feature point, in the first image. A Hough transform technique is designed to detect this intersection point and track the corresponding feature points in the image sequence. This technique is suitable for tracking a large number of feature points. Its performance is practically unaffected by missing features in some images and large motion steps. Accurate and reliable results had been obtained in real experiments using the method.

关键词： Mobile robots

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Object-oriented vision for a behavior-based robot

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 1996年 2904卷 278-289页

作者： Bischoff, Rainer Graefe, Volker Wershofen, Klaus P. Federal Armed Forces Univ. Munich Neubiberg Ger Germany

ISBN: (纸本)0819423068

As one realization out of the class of behavior-based robot architectures a specific concept of situation-oriented behavior-based navigation has been proposed. Its main characteristic is that the selection of the behaviors to be executed in each moment is based on a continuous recognition and evaluation of the dynamically changing situation in which the robot is finding itself. An important prerequisite for such as approach is a timely and comprehensive perception of the robot's dynamically changing environment. Object-oriented vision as proposed and successfully applied, e.g., in freeway traffic scenes is a particularly well suited sensing modality for robot control. Our work concentrated on modeling the physical objects which are relevant for indoor navigation, i.e. walls, intersections of corridors, and landmarks. In the interest of efficiency these models include only those necessary features for allowing the robot to reliably recognize different situations in real time. According to the concept of object-oriented vision recognizing such objects is largely reduced to a knowledge-based verification of objects or features that may be expected to be visible in the current situation. The following results have been achieved: 1) By using its vision system and a knowledge base in the form of an attributed topological map the robot could orient itself and navigate autonomously in a known environment. 2) In an unknown environment the robot was able to build, by means of supervised learning, an attributed topological map as a basis for subsequent autonomous navigation. 3) The experiments could be performed both under unmodified artificial light and under natural light shining through the glass walls of the building.

关键词： computer vision

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Line following using a two camera guidance system for a mobile robot

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 1996年 2904卷 290-297页

作者： Samu, Tayib Kelkar, Nikhal Perdue, David Ruthemeyer, Michael A. Matthews, Bradley O. Hall, Ernest L. Univ. of Cincinnati Cincinnati OH USA

ISBN: (纸本)0819423068;9780819423061

Automated unmanned guided vehicles have many potential applications in manufacturing, medicine, space and defense. A mobile robot has been designed for the 1996 Automated Unmanned Vehicle Society competition which was held in Orlando, Florida on July 15, 1996. The competition required the vehicle to follow solid and dashed lines around an approximately 800 ft. path while avoiding obstacles, overcoming terrain changes such as inclines and sand traps, and attempting to maximize speed. The purpose of this paper is to describe the algorithm developed for the line following. The line following algorithm images two windows and locates their centroid and with the knowledge that the points are on the ground plane, a mathematical and geometrical relationship between the image coordinates of the points and their corresponding ground coordinates are established. The angle of the line and minimum distance from the robot centroid are then calculated and used in the steering control. Two cameras are mounted on the robot with a camera on each side. One camera guides the robot and when it loses track of the line on its side, the robot control system automatically switches to the other camera. The test bed system has provided an educational experience for all involved and permits understanding and extending the state of the art in autonomous vehicle design.

关键词： Mobile robots

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Cavity surface measuring system using stereo reconstruction

Proceedings of SPIE - The International Society for Optical ...

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Proceedings of SPIE - The International Society for Optical Engineering 1996年 2904卷 207-217页

作者： Paar, Gerhard Bauer, A. Joanneum Research Inst. Graz Austria

ISBN: (纸本)0819423068;9780819423061

3D reconstruction of highly textured surfaces on unvegetated terrain is of major interest for stereo vision based mapping applications. We describe a prototype system for automatic modeling of such scenes. It is based on two frame CCD cameras, which are tightly attached to each other ensuring constant relative orientation. One camera is used to acquire known reference points to get the exterior orientation of the system, the other records the surface images. The system is portable to keep image acquisition as short as possible. Automatic calibration using the images acquired by the calibration camera permits the computation of exterior orientation parameters of the surface camera via a transformation matrix. A robust matching method providing dense disparities together with a flexible reconstruction algorithm renders an accurate grid of 3D points on arbitrarily shaped surfaces. The results of several stereo reconstructions are merged. Projection onto the global shape allows easy evaluation of volumes, and thematic mapping with respect to the desired surface geometry in construction processes. We report on accuracy and emphasize on the practical usage. It is shown that the prototpye system is able to generate a proper data set of surface descriptions that is accurate and dense enough to serve as documentation, planning and accounting basis.

关键词： Binocular vision

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