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检索条件"任意字段=Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3-D Methods"

共 113 条记录，以下是81-90 订阅

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FUSION BASEd dEPTH ESTIMATION FROM A SEQUENCE OF MONOCULAR IMAGES 10

FUSION BASED DEPTH ESTIMATION FROM A SEQUENCE OF MONOCULAR I...

引用

CONF ON intelligent robots ANd computer vision 10 : neural, biological, and 3-d methods

作者： SHIEH, JY ZHUANG, HQ SUdHAKAR, R Florida Atlantic Univ. (United States)

ISBN: (纸本)0819407453

This paper reports the development of a general depth estimation system directly using image sequence. We combine the direct depth estimation method with the optical flow based method. More specifically, the optical flow on or near moving edges are computed using a correlation technique. The optical flow information is then fused with gradient information to estimate depth not only on moving edges but also in internal regions. The depth estimation problem is formulated as a discrete Kalman filter problem and is solved in three stages. In the prediction stage, the depth map estimated for the current frame, together with knowledge of the camera motion, are used to predict the depth variance at each pixel in the next frame. In the estimation stage, a vector-version of Kalman filter formulation is adopted and then simplified under the assumption of a diagonized error covariance. The resulting estimation algorithm takes into account of the information from the neighboring pixels and therefore is much more robust than the scalar-version Kalman filter implementation. In the smoothing stage, morphological filtering is applied to the estimated depth map to reduce the measurement noise and fill in the untrustable areas based on the error covariance information. Simulation results illustrate the effectiveness of the presented method.

关键词： Optical flow Filtering (signal processing) Robot vision Motion estimation Cameras Machine vision computer vision technology Error analysis Signal to noise ratio Image filtering

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A SINGLE INSTRUCTION computer ARCHITECTURE ANd ITS APPLICATION IN IMAGE-PROCESSING 10

A SINGLE INSTRUCTION COMPUTER ARCHITECTURE AND ITS APPLICATI...

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CONF ON intelligent robots ANd computer vision 10 : neural, biological, and 3-d methods

作者： LAPLANTE, PA Fairleigh Dickinson University Madison Ave. Madison 07940 NJ United States

ISBN: (纸本)0819407453

A single processing computer system using only half-adder circuits is described. In addition, it is shown that only a single hard-wired instruction is needed in the control unit to obtain a complete3 instruction set for this general purpose computer. Such a system has several advantages. First it is intrinsically a RISC machine - in fact the "ultimate RISC" machine. Second, because only a single type of logic element is employed the entire computer system can be easily realized on a single, highly integrated chip. Finally, due to the homogeneous nature of the computer's logic elements, the computer has possible implementations as an optical or chemical machine. This in turn suggests possible paradigms for neural computing and artificial intelligence. After showing how we can implement a full-adder, min, max and other operations using the half-adder, we use an array of such full-adders to implement the dilation operation for two black and white images. Next we implement the erosion operation of two black and white images using a relative complement function and the properties of erosion and dilation. This approach was inspired by papers by van der Poel⁸ in which a single instruction is used to furnish a complete set of general purpose instructions and by Bohm-Jacopini where it is shown that any problem can be solved using a Turing machine with one entry and one exit¹ © 1992 SPIE. All rights reserved.

关键词： Optical data processing

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IMPROVING THE ROBUSTNESS OF EdGE ANd REGION-BASEd RANGE IMAGE SEGMENTATION 10

IMPROVING THE ROBUSTNESS OF EDGE AND REGION-BASED RANGE IMAG...

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CONF ON intelligent robots ANd computer vision 10 : neural, biological, and 3-d methods

作者： KOIVUNEN, V PIETIKAINEN, M Univ. of Oulu (Finland)

ISBN: (纸本)0819407453

In our previous work, we presented a segmentation method that combines useful properties of edge and region-based segmentation. In the region-based approach, pixels are classified into 10 surface types according to the spatial properties in the neighborhood of each pixel. Surface differential properties are approximated using least squares estimation. Geometrically coherent regions are formed by grouping connected pixels of the same surface type. A two stage method which detects both step and roof edges is used for edge detection. Preliminary edge and region-based segmentation results are overlaid to achieve the final segmentation. This paper presents our recent results which improve the robustness of the segmentation method. Accurate estimation of the differential properties of the surfaces is essential if one is to gain good segmentation. The least squares estimation with constant coefficient window operators gives good results when only white Gaussian distributed noise occurs, and pixels in the neighborhood are from one statistical population. In order to decrease the influence of very deviant pixel values that occur near region boundaries or due to noise, we implemented two robust estimation methods. One is iterative reweighting least squares method that uses a variable order model and the other is a least trimmed square method. The robust and least squares approaches are compared and their effects on surface classification are reported. Also the validity of the assumptions on the data, model and estimation methods used are considered. Both synthetic and real range images are used for test images.

关键词： Image segmentation data modeling Statistical analysis computer vision technology Image quality Machine vision robots Signal attenuation Error analysis Robot vision

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PARALLEL RANGE dATA-PROCESSING - A REAL CASE-STUdY 10

PARALLEL RANGE DATA-PROCESSING - A REAL CASE-STUDY

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CONF ON intelligent robots ANd computer vision 10 : neural, biological, and 3-d methods

作者： SLUdER, JC ABIdI, MA Univ. of Tennessee/Knoxville (United States)

ISBN: (纸本)0819407453

In this paper, we begin by describing a range image processing method developed to allow an autonomous robot to detect and locate objects. The procedure consists of taking a range image, filtering and preprocessing the image, calculating surface normals, obtaining edge maps from both range and surface normals, combining the edge maps into an initial scene segmentation map, and analyzing each object in the scene in order to detect and locate the desired objects. While this method is reasonably fast and robust, its surface characterization is fairly crude. More elaborate surface characterization on a serial computer would be considerably slower, which is not desirable for autonomous robot operations. We then discuss the development of parallel techniques for surface characterization using range data. By using parallel processing, the complexity and accuracy of the characterization can be increased without an unacceptable cost in processing time. The method explored is a parallel implementation of a least squares QR surface fitting technique using Givens transformations. We conclude by summarizing the work done and briefly listing some future extensions of the current research.

关键词： Image filtering Robot vision digital filtering Laser scanners Image segmentation Image processing computer vision technology Laser range finders Machine vision Optical filters

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Location of polyhedral objects in 3-d space from three unconstrained edge points 10

Location of polyhedral objects in 3-D space from three uncon...

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intelligent robots and computer vision X: neural, biological, and 3-d methods 1991

作者： Bunke, Horst Lim, Hong-Seh Meier, Urs Institut fuer Informatik und Angewandte Mathematik Laenggassstrasse 51 BerneCH-3012 Switzerland Calera Recognition System Inc. 475 Potrero Avenue SunnyvaleCA94086 United States

We present algorithms for locating polyhedral objects using three edge points. An edge point is a three-dimensional data point which lies on a known edge of an object. In this paper, we assume that the precise position of an edge point on an edge is not known. In general, with three edge points, we have to solve a system of nonlinear equations. However, there are special cases, where we can solve the location problem analytically. The special cases depend on the collinearity and coplanarity of the three edge points. © 1992 SPIE. All rights reserved.

关键词： Location

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Finding cones from multi-scan range maps 10

Finding cones from multi-scan range maps

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intelligent robots and computer vision X: neural, biological, and 3-d methods 1991

作者： Lejun, Shao Volz, Richard School of Electrical and Electronic Engineering Nanyang Technological University Singapore2263 Singapore Computer Science Department Texas A and M University College StationTX77843 United States

Two algorithms are presented to locate a cone with a known shape from a range scan map. They are ellipse fitting and three-scan methods. The localization problem includes the finding of both cone's orientation and displacement relative to the sensing coordinate system. The work described in this paper is an extension to the problem of extracting the cylinder parameters from a depth scan map. The range data are obtained from either a light-stripe based range sensor or a line range sensor, which measures the distance between the sensor and the nearest points on the intersection of the light plane and the scene. The three-scan method uses range data from three scan lines of measurements. It does not use any ellipse fitting. This method first extracts the orientation parameters of at least three cone's generators and then derive the axis direction vector from the cone's generators. The performance of this method is compared with the usual ellipse fitting method. © 1992 SPIE. All rights reserved.

关键词： Geometry

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A three-dimensional object representation based on the laigest convex patches method 10

A three-dimensional object representation based on the laige...

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intelligent robots and computer vision X: neural, biological, and 3-d methods 1991

作者： Zlateva, Stoyanka Vaina, Lucia M. Intelligent Systems Laboratory Boston Univeristy ERB-336 44 Cummington str. BostonMA02215 United States College of Engineering Metropolitan Collge Boston Univeristy ERB-336 44 Cummington str. BostonMA02215 United States

We introduce a representation of three dimensional (3d) shape of objects which describes object shape through configurations of interrelated parts and accounts for their surface and volumetric properties as well. The decomposition into constituent parts is obtained by an earlier developed surfaced based method that uses the largest locally convex patches (LCP) and the largest everywhere nonconvex patches to characterize and define part boundaries. This characteristization of the part boundary provides the basis for assigning to each part a simple volumetric primitive that preserves its surface type. We propose a heuristics for choosing the volumetric description motivated by a teorem from differential geometry which classifies surface points (elliptic, hyperbolic, parabollic, plane) through the type of the parabolloid that approximates a finite *** provides a natural way of relating surface properties of the boundary based decomposition to volumetric properties of the primitive based part description. A further decomposition into subparts and the computation of associated features on a "if needed" basis allow to account for structural details which appear to be closely related to the use of the object in actions. We present examples of the shape descriptions of various machine tools and show that the parts and subparts computed by the representation directly relate to affordances of the object. © 1992 SPIE. All rights reserved.

关键词： Machine tools

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intelligent robots and computer vision IX: neural, biological, and 3-d methods

Intelligent Robots and Computer Vision IX: Neural, Biologica...

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intelligent robots and computer vision IX: neural, biological, and 3-d methods

This Conference Proceedings contains 41 papers grouped in four sessions dealing with: neuronal-morphology of biological vision as a basis for machine vision;neural networks for intelligent systems;reconstruction, description and modeling of 3-d images;three-dimensional scene perception. Some of the topics discussed are the following: neural model for feature matching in stereo vision;new perspectives for vision enhancement for the visually impaired;receptive fields and the theory of discriminant operators;determining range information from self-motion;on-line visual prosthetics for a decision maker;Ho-Kashyap associative processors;motion analysis for visually guided navigation;connectionist learning system for control;space-time system architecture for the neural optical computing;statistical and neural network classifiers in model-based 3-d object recognition;iterative neural networks for skeletonization and thinning;neural edge detectors;reconstruction during camera fixation;three-dimensional reconstruction from optical flow using temporal integration;three-dimensional description of symmetric objects from range images;topographic mapping for stereo and motion processors;evaluation of a pose estimation algorithm using single perspective view;range data from stereo images of edge points.

关键词： computer vision

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RECEPTIVE-FIELdS ANd THE THEORY OF dISCRIMINANT OPERATORS

RECEPTIVE-FIELDS AND THE THEORY OF DISCRIMINANT OPERATORS

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9TH CONF ON intelligent robots ANd computer vision : neural, biological, ANd THREE-dIMENSIONAL methods

作者： GUPTA, MM HUNGENAHALLY, SK Univ of Saskatchewan Saskatoon Canada

ISBN: (纸本)0819404497

biological basis for machine vision is a notion which is being used extensively for the development of machine vision systems for various applications. In this paper we have made an attempt to emulate the receptive fields that exist in the biological visual channels. In particular, we have exploited the notion of receptive fields for developing the mathematical functions named as discriminant functions, for the extraction of transition information from signals and multi-dimensional signals and images. These functions are found to be useful for the development of artificial receptive fields for neuro-vision systems.

关键词： computer vision

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3-d vision ANd FIGURE GROUNd SEPARATION BY VISUAL-CORTEX

3-D VISION AND FIGURE GROUND SEPARATION BY VISUAL-CORTEX

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9TH CONF ON intelligent robots ANd computer vision : neural, biological, ANd THREE-dIMENSIONAL methods

作者： GROSSBERG, S Boston Univ Boston United States

ISBN: (纸本)0819404497

A theory of 3-d visual perception and figure/ground separation by visual cortex is described. Called FACAdE Theory, it suggests a solution of the 3-d figure/ground problem for biological vision and makes many predictions whereby it can be tested. The theory further develops my 3-d vision theory of 1987, which used multiple receptive field sizes, or scales, to define multiple copies of two interacting systems: a Boundary Contour System (BCS) for generating emergent boundary segmentations of edges, textures, and shading;and a Feature Contour System (FCS) for discounting the illuminant and filling in surface representations of Form-And-Color-And-dEpth, or FACAdEs. The 1987 theory did not posit interactions between the several scales of the BCS and FCS. The present theory suggests how competitive and cooperative interactions, that were previously defined within each scale, also act between scales.

关键词： vision

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