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A general-purpose platform for 3-D reconstruction from sequence of images

A general-purpose platform for 3-D reconstruction from seque...

引用

5th International Conference on Information Fusion, FUSION 2002

作者： Eid, Ahmed H. Rashad, Sherif S. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0972184414

A number of approaches have been proposed in the literature for reconstruction of 3-D objects from sequence of images. Yet, very few studies have been reported on the quantification/validation of the accuracy of these reconstructions. In addition, no design has been reported for a generic vision platform that can allow various modality imaging. The purpose of this paper is two folds: 1) propose a vision platform that lend itself for acquisition of calibrated sequence of images, and concurrently obtain a direct 3-D reconstruction by laser scanning;and 2) develop and implement different approaches for 3-D reconstructions from sequence of images. 3-D reconstructions will be evaluated against the 3-D scanning generated from a laser scanner. Validation of the reconstructions is made by pairwise comparison with the 3-D scanning results. Preliminary studies with the proposed vision platform show a good promise for its use in the validation of various 3-D reconstructions, registration and data fusion. © 2002 Int. Soc. of Information Fusion.

关键词： Scanning

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Experiments in multimodality image classification and data fusion

Experiments in multimodality image classification and data f...

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5th International Conference on Information Fusion, FUSION 2002

作者： Farag, Aly A. Mohanied, Refaat M. Mahdi, Hani Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0972184414

In this paper, we report the results of some experiments on image classification and data fusion of remote sensing images, as part of ongoing efforts at the CVIP to develop a general strategy for the analysis of multimodality imaging. Statistical and Fuzzy logic approaches have been employed in these experiments. In all, six different algorithms for image classification, and an image fusion algorithm have been implemented and evaluated on common data sets. These algorithms are: (1) Supervised Parametric Bayes Classifier;(2) Non-parametric Bayesian Classifier using the Parzen density estimate;(3) Maximum a posteriori classification using the k-nearest neighbors (k-NN) approach;(4) MAP Estimation using Markov random field modeling;(5) a Fuzzy logic approach;and (6) a novel discriminate function classifier. The AMP segmentation of the regions in the image has been implemented using the Iterated Conditional Mode (ICM) optimization method. This approach provided the best results, in terms of the minimum probability of error and best reliability. A novel decision fusion algorithm, based on the a priori class conditional probability, has been applied to the classifiers' output. © 2002 Int. Soc. of Information Fusion.

关键词： Fuzzy logic

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Resolving ambiguity in depth extraction for motion capture using genetic algorithm

Resolving ambiguity in depth extraction for motion capture u...

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2002 Congress on Evolutionary Computation, CEC 2002

作者： Wai, Yin Yee Chow, Chi Kin Lee, Tong Computer Vision and Image Processing Laboratory Dept. of Electronic Engineering Chinese University of Hong Kong Shatin Hong Kong

ISBN: (纸本)0780372824

There is considerable interest in motion capture from an image sequence taken from a video camera. However, since the images only consist of 2D information, the distance of an object from the image plane cannot be determined uniquely unless some constraints are imposed. Coplanar motion is a popular constraint adopted for this purpose. If the captured motion is not coplanar, only two possible solutions can be obtained at the best even the actual size of the object is given. Therefore, the motion cannot be captured without resolving the distances of each control point from the image plane. By assuming smooth transition, the problem is formulated as one minimizing the transition between image frames and the application of GA to solve this optimization problem is proposed. © 2002 IEEE.

关键词： Video cameras

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Experiments in multimodality image classification and data fusion

Experiments in multimodality image classification and data f...

引用

International Conference on Information Fusion

作者： A.A. Farag R. Mohamed H. Mahdi Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Computer Vision and Image Processing Laboratory University of Louisville Louisville KY

In this paper, we report the results of some experiments on image classification and data fusion of remote sensing images, as part of ongoing efforts at the CVIP to develop a general strategy for the analysis of multimodality imaging. Statistical and Fuzzy logic approaches have been employed in these experiments. In all, six different algorithms for image classification, and an image fusion algorithm have been implemented and evaluated on common data sets. These algorithms are: (1) Supervised Parametric Bayes Classifier; (2) Non-parametric Bayesian Classifier using the Parzen density estimate; (3) Maximum a posteriori classification using the k-nearest neighbors (k-NN) approach; (4) MAP Estimation using Markov random field modeling; (5) a Fuzzy logic approach; and (6) a novel discriminate function classifier. The AMP segmentation of the regions in the image has been implemented using the Iterated Conditional Mode (ICM) optimization method. This approach provided the best results, in terms of the minimum probability of error and best reliability. A novel decision fusion algorithm, based on the a priori class conditional probability, has been applied to the classifiers' output.

关键词： image classification Fuzzy logic Remote sensing image analysis Classification algorithms image fusion Bayesian methods Markov random fields image segmentation Optimization methods

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A general-purpose platform for 3-D reconstruction from sequence of images

A general-purpose platform for 3-D reconstruction from seque...

引用

International Conference on Information Fusion

作者： A.H. Eid S.S. Rashad A.A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville USA

A number of approaches have been proposed in the literature for reconstruction of 3-D objects from sequence of images. Yet, very few studies have been reported on the quantification/validation of the accuracy of these reconstructions. In addition, no design has been reported for a generic vision platform that can allow various modality imaging. The purpose of this paper is two folds: 1) propose a vision platform that lend itself for acquisition of calibrated sequence of images, and concurrently obtain a direct 3-D reconstruction by laser scanning; and 2) develop and implement different approaches for 3-D reconstructions from sequence of images. 3-D reconstructions will be evaluated against the 3-D scanning generated from a laser scanner. Validation of the reconstructions is made by pairwise comparison with the 3-D scanning results. Preliminary studies with the proposed vision platform show a good promise for its use in the validation of various 3-D reconstructions, registration and data fusion.

关键词： Three dimensional displays image reconstruction Head Cameras Stereo image processing Laser modes image segmentation computer vision image processing Laboratories

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Monocular, vision based, autonomous refueling system

Monocular, vision based, autonomous refueling system

引用

IEEE Workshop on Applications of computer vision (WACV)

作者： A. Farag E. Dizdarevic A. Eid A. Lorincz Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA

This paper describes design and implementation of a vision based platform for automated refueling tasks. The platform is an autonomous docking system in principle, with the specific application - refueling of vehicles. The system is. based on monochromatic, monocular vision, and it utilizes very specialized image processing schemes. image processing consists of very fast filtering and segmenting algorithms, as well as moment's computation. A robotic arm with 6 joints (FANUC M-6i), and a controller unit (R-B), does the physical work. A serial interface, with very high-level commands, connects a supercomputing machine and the robot's controller. A practical setup would probably be scaled down to a special design robot, and a single processor, controller with special VLSI chips for image processing. Results are very promising; the robot can identify the cap position, orientation, and height in real time with acceptable accuracy and reliability.

关键词： image processing Robot vision systems Cameras Robotics and automation Shape computer vision Laboratories image segmentation Robot control Vehicles

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Fast recovery of piled deformable objects using superquadrics

Fast recovery of piled deformable objects using superquadric...

引用

24th German Association for Pattern Recognition Symposium, DAGM 2002

作者： Katsoulas, Dimitrios Jaklič, Aleš Institute for Pattern Recognition and Image Processing University of Freiburg Georges-Koehler-Allee 52 FreiburgD-79110 Germany Computer Vision Laboratory University of Ljubljana Tržaška cesta 25 LjubljanaSI-1000 Slovenia

ISBN: (纸本)354044209X

Fast robotic unloading of piled deformable box-like objects (e.g. box-like sacks), is undoubtedly of great importance to the industry. Existing systems although fast, can only deal with layered, neatly placed configurations of such objects. In this paper we discuss an approach which deals with both neatly placed and jumbled configurations of objects. We use a time of flight laser sensor mounted on the hand of a robot for data acquisition. Target objects are modeled with globally deformed superquadrics. Object vertices are detected and superquadric seeds are placed at these vertices. Seed refinement via region growing results in accurate object recovery. Our system exhibits a plethora of advantages the most important of which its speed. Experiments demonstrate that our system can be used for object unloading in real time, when a multi-processor computer is employed. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Data acquisition

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Construction of multi-layer feedforward binary neural network by a genetic algorithm

Construction of multi-layer feedforward binary neural networ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Chi Kin Chow Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China

An approach is introduced to determine the topology of a feedforward binary neural network automatically. The approach is based on a construction algorithm that constructs one layer of hidden nodes at a time until the problem is solved. In each layer, the algorithm determines the necessary number of nodes through a growth process by finding the best hidden node that would help to partition the input training data set. This is done using a genetic algorithm. The proposed algorithm can determine the necessary number of hidden layers and number of hidden nodes at each layer automatically. Tests on a number of benchmark problems illustrated the effectiveness of the proposed technique, both in terms of network complexity and recognition accuracy, compared with a geometrical learning approach.

关键词： Neural networks Multi-layer neural network Feedforward neural networks Genetic algorithms Network topology Partitioning algorithms Training data Error correction computer vision image processing

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Invariant feature matching by Hopfield-type neural network

Invariant feature matching by Hopfield-type neural network

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International Joint Conference on Neural Networks (IJCNN)

作者： Wen-Jing Li Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China

In this paper, a novel Hopfield model for silhouette matching invariant to projective transformations is proposed. Although the new network has higher-order energy function, we show that it can be solved using a standard second-order Hopfield network, by taking advantage of the neighborhood information in the data. The experimental results with real data show that the proposed method can provide accurate matching results in image registration and object recognition.

关键词： Neural networks Hopfield neural networks Object recognition Power engineering and energy Stereo vision Motion estimation Feature extraction Cost function Layout computer vision

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Resolving ambiguity in depth extraction for motion capture using genetic algorithm

Resolving ambiguity in depth extraction for motion capture u...

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Congress on Evolutionary Computation

作者： Yin Yee Wai Chi Kin Chow Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Sha Tin Hong Kong China

关键词： Genetic algorithms Humans Cameras image resolution image sequences Animation Motion analysis Optical filters Optical recording Optical sensors

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