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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41-50 订阅

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HIERARCHICAL neural netWORKS FOR EdGE PRESERVATION ANd RESTORATION 10

HIERARCHICAL NEURAL NETWORKS FOR EDGE PRESERVATION AND RESTO...

引用

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

作者： LU, SW SZETO, A Memorial Univ. of Newfoundland (Canada)

ISBN: (纸本)0819407453

In the paper, a hierarchical neural network system is designed to adjust edge measurements based on the information provided by neighboring edges. The local edge pattern is analyzed to determine and reinforce edge structures while suppressing unwanted noise and false edges. The neural network is made up of four levels of subnets. The subnet in the first level determines the potential adjustment on the element of interest by detecting edge contours according to the selected processes in the neural nets and the input local edge pattern. The second level consists of a cooperative-competitive neural net model to find the orientation of the strongest edge contour in the local edge pattern. The subnet in the third level ascertains the conditions for adjusting the gradient magnitude and determines the amount of adjustment to the gradient magnitude, and calculates the new adjusted gradient magnitude and determines if the element of interest is to be an edge element or a non-edge element. The subnet in level four is a semilinear feedforward net which is used to assign the new orientation for the element of interest. An iterative approach incorporated into the neural network system has also enabled the application of global analysis in the process of adjusting the edge measurements.

关键词： neural networks Robot vision Edge detection computer vision technology Machine vision Process modeling Aluminum Computing systems Image processing Image enhancement

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HANdWRITTEN dIGIT RECOGNITION USING neural netWORKS 10

HANDWRITTEN DIGIT RECOGNITION USING NEURAL NETWORKS

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

作者： BISCHOFF, A WANG, PSP Northeastern Univ. (United States)

ISBN: (纸本)0819407453

Character and handwriting recognition is one of the most difficult problems of pattern recognition and artificial intelligence. Unlike the machine generated character, which is uniform throughout a document and often uniform between machines, each human being has a unique style of writing characters. With the infinite number of ways to record a character, it is a wonder that a person can understand his own script, let alone the script of another. Training a computer to recognize human-produced characters is a tremendous task in which researchers are just beginning to achieve some success. Primarily these methods rely on the use of algorithms to determine the similarities of two characters. neural networks are an alternative technique now being explored. Four separate methods will be discussed in this paper. The first involves normalization, skeletonization, and feature extraction of a handwritten digit before application to a neural network for classification. The second simply applies a normalized digit to the neural net's input, and the network performs a 2-dimensional convolution on it in order to classify the digit. The third method involves a hierarchical network. The final technique incorporates time information into the system while using simple preprocessing and a small number of parameters. Their advantages and disadvantages are compared and discussed.

关键词： neural networks computer vision technology Machine vision Robot vision robots Feature extraction Pattern recognition Machine learning network architectures Neurons

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TRINOCULAR vision - A 3-d SOLUTION 10

TRINOCULAR VISION - A 3-D SOLUTION

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

作者： BORTOLOZZI, F dUBUISSON, B Compiegne Univ. (France)

ISBN: (纸本)0819407453

This paper presents a solution for the following problems: matching between trinocular images, full reconstruction of 3-d segments without the length constraint, elimination of false triplets. In a first step, cameras are calibrated. This provides high precision perspective transformation matrices and defines the geometry of the system. This approach is used to help the perception of a mobile robot. Our approach for matching is a geometry-based one.

关键词： Image segmentation Cameras 3d vision robots computer vision technology Machine vision Robot vision Imaging systems Matrices 3d image processing

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computer vision: Reconstructing 3-d model from 2-d images 10

Computer vision: Reconstructing 3-D model from 2-D images

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

作者： Tan, Zheng Long, Gong Dept. of Information and Control Engineering Xi'an Jiao Tong University 710049 China

A comprehensive algorithm for the reconstruction of three dimensional model from a pair of two dimendional images is presented in this paper. The dynamic programming matching based on "bridging method" are guided by the results of feature based matching. In the process of feature based matching, the mathematic morphology is introduced to describe the feature extracted *** those area without distinct feature point, area based correlation is applied to get the fine location of the corresponding *** last, the constraints in two directions is introduced to check out the mismatched points. © 1992 SPIE. All rights reserved.

关键词： computer vision

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A NEW FAST ANd ACCURATE RECONSTRUCTION METHOd OF 3d PLANES 10

A NEW FAST AND ACCURATE RECONSTRUCTION METHOD OF 3D PLANES

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

作者： BONNIN, P ZAVIdOVIQUE, B ETCA/CREA/SP 16 bis Av Prieur de la Côte d'Or Arcueil Cétex 94114 France ETCA/CREA/SP University of Paris XI I.E.F bat 220 Orsay 91405 France

ISBN: (纸本)0819407453

This paper describes a 3d reconstruction method of polyhedric objects (planar faces), that uses planarity constraints. Not very often used on papers, because of its global nature, we propose a new global/local implementation of these constraints. It is detailled in the context of our-edge-region cooperative segmentation. Conceptually, the advantages of this method are its simplicity, a precise knowledge of its incertaincies, and at the operationnal level its rapidity and the preciseness of the obtained volumetric reconstruction. © 1992 SPIE. All rights reserved.

关键词： Image reconstruction

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THE ENTROPY CONSISTENCY PRINCIPLE IN BINOCULAR STEREOPSIS 10

THE ENTROPY CONSISTENCY PRINCIPLE IN BINOCULAR STEREOPSIS

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

作者： ZHAO, Y Department of Computer Science Trinity College Dublin Ireland

ISBN: (纸本)0819407453

This paper presents a new theoretical entropy formalism to stereo vision - an entropy view of stereopsis. At the heart of this formalism is the entropy consistency principle. It reflects the essential "active" and "dynamic" nature of binocular stereo vision process. Finally, an experimental stereo system based on mathematical morphology is proposed and is integrated into the entropy formalism presented in this paper. © 1992 SPIE. All rights reserved.

关键词： Entropy

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vision MOdELS FOR 3d SURFACES

VISION MODELS FOR 3D SURFACES

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11TH CONF ON intelligent robots ANd computer vision : biological, neural net, and 3-d methods

作者： MITRA, S Texas Tech Univ. (United States)

ISBN: (纸本)0819410276

different approaches to computational stereo to represent human stereo vision have been developed over the past two decades. The Marr-Poggio theory of human stereo vision is probably the most widely accepted model of the human stereo vision. However, recently developed motion stereo models which use a sequence of images taken by either a moving camera or a moving object provide an alternative method of achieving multi-resolution matching without the use of Laplacian of Gaussian operators. While using image sequences, the baseline between two camera positions for a image pair is changed for the subsequent image pair so as to achieve different resolution for each image pair. Having different baselines also avoids the inherent occlusion problem in stereo vision models. The advantage of using multi-resolution images acquired by camera positioned at different baselines over those acquired by LOG operators is that one does not have to encounter spurious edges often created by zero-crossings in the LOG operated images. Therefore in designing a computer vision system, a motion stereo model is more appropriate than a stereo vision model. However, in some applications where only a stereo pair of images are available, recovery of 3d surfaces of natural scenes are possible in a computationally efficient manner by using cepstrum matching and regularization techniques. Section 2 of this paper describes a motion stereo model using multi-scale cepstrum matching for the detection of disparity between image pairs in a sequence of images and subsequent recovery of 3d surfaces from depth-map obtained by a non convergent triangulation technique. Section 3 presents a 3d surface recovery technique from a stereo pair using cepstrum matching for disparity detection and cubic B-splines for surface smoothing. Section 4 contains the results of 3d surface recovery using both of the techniques mentioned above. Section 5 discusses the merit of 2d cepstrum matching and cubic B-spline interpolation

关键词： 3d modeling Motion models Visual process modeling 3d vision Stereo vision systems Cameras Human vision and color perception 3d image processing Computing systems Machine vision

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neural netWORK MOdELING OF NEW ENERGY FUNCTION FOR STEREO MATCHING 10

NEURAL NETWORK MODELING OF NEW ENERGY FUNCTION FOR STEREO MA...

引用

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

作者： LEE, JJ CHO, SJ HA, YH Kyungpook National Univ. (South Korea)

ISBN: (纸本)0819407453

In vision research, most problems can be modeled as minimizing an energy function. Particularly, stereo matching can be viewed as one of the optimization problems in which the constraints must be satisfied simultaneously. neural networks have been demonstrated to be very effective in computing these problems. In this paper, an approach to solve the stereo matching problem using the neural network with a new energy function is presented. The new energy function is derived not only to satisfy three constraints of similarity, smoothness, and uniqueness, but also to ensure Hopfield's convergence rules of symmetrical interconnection strength without self-feedback. Experimental results shows good stereo matching for sparse random dot stereograms and real images.

关键词： Neurons neural networks computer vision technology Machine vision Robot vision robots Visual process modeling Stereo holograms Infrared imaging Holmium

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STEREO-BASEd 3-d SCENE INTERPRETATION USING SEMANTIC netS 10

STEREO-BASED 3-D SCENE INTERPRETATION USING SEMANTIC NETS

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

作者： RONING, JH TAIPALE, TP Univ. of Oulu (Finland) Technical Research Ctr. of Finland (Finland)

ISBN: (纸本)0819407453

A SCene INterpreter system, SCIN, for indoor scenes has been developed as a part of an autonomous navigation project at the University of Oulu. Starting from passive stereo, SCIN gradually forms a scene graph utilizing semantic net representation. In the graph formation, bottom-up and top-down approaches are combined with the exploitation of a priori information from the environment. The interpretation is done by matching model graphs to the scene graph, and gradually refining the scene graph towards a higher level symbolic representation. The refinement is done by balancing between replacement and an addition of a new node. The model graphs represent different kinds of entities the system is supposed to find from a scene. The complexity of the used model graphs grows as the analysis proceeds. This paper describes the structure of the scene graph, and the model graphs, and the benefits of this representation. The matching and refining of the scene graph are also explained. Experimental results using a robot arm and an indoor robot vehicle are presented to verify the operation of the interpreter.

关键词： Image segmentation 3d modeling Visual process modeling Robot vision data modeling Cameras Navigation systems 3d image processing computer vision technology Machine vision

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HOUGH TRANSFORM FOR 3-d OBJECT RECOGNITION 10

HOUGH TRANSFORM FOR 3-D OBJECT RECOGNITION

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

作者： CAO, XP HU, GZ Central Michigan Univ. (United States)

ISBN: (纸本)0819407453

This paper describes an approach to the recognition of objects of known shapes by matching, in the Hough space, the features (edges and normal vectors) extracted from range images to object models. The matching is carried out in hierarchy. First, a few candidate rotation matrices are determined based on the peaks in the Hough accumulator that represents the orientation of a reference vector. Then the translation parameters are evaluated for each rotation matrix, and the transformation is obtained based on the best interpretation between the model and the scene. The experiments indicate that the procedure is accurate, although optimization can further improve the estimates of the parameters.

关键词： 3d modeling Visual process modeling Hough transforms data modeling computer vision technology Machine vision Robot vision robots Object recognition 3d image processing

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