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Experiments in multimodality image classification and data fusion

Experiments in multimodality image classification and data f...

引用

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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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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Resolving ambiguity in depth extraction for motion capture using genetic algorithm

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

引用

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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Head detection and localization from sparse 3D data

Head detection and localization from sparse 3D data

引用

24th German Association for Pattern Recognition Symposium, DAGM 2002

作者： Clabian, Markus Rötzer, Harald Bischof, Horst Kropatsch, Walter Advanced Computer Vision GmbH Donau City Str.1 ViennaA-1220 Austria Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16 GrazA-8010 Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department Vienna University of Technology Favoritenstr. 9 ViennaA-1040 Austria

ISBN: (纸本)354044209X

Head detection is an important, but difficult task, if no restrictions such as static illumination, frontal face appearance or uniform background can be assumed. We present a system that is able to perform head detection under very general conditions by employing a 3D measurement system namely a structured light distance measurement. An algorithm of head detection from sparse 3D data (19x19 data points) is developed that reconstructs a 3D surface over the image plane and detects head hypotheses of ellipsoidal shape. We demonstrate that detection and rough localization is possible in up to 90% of the images. © Springer-Verlag Berlin Heidelberg 2002.

关键词： computers

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Multiple objects segmentation based on maximum-likelihood estimation and optimum entropy-distribution(MLE-OED)

Multiple objects segmentation based on maximum-likelihood es...

引用

16th International Conference on Pattern Recognition, ICPR 2002

作者： Jun, Xie Tsui, H.T. Deshen, Xia Image Processing and Computer Vision Lab Department of Electronic Engineering Chinese University of Hong Kong Hong Kong Pattern Recognition Lab Department of Computer Science Nanjing University of Sci.andTech. China

ISBN: (纸本)0769516963

A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties . The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples Its performance in the experiments is better than those of two popular methods. © 2002 IEEE.

关键词： Maximum likelihood estimation

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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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Hierarchical top down enhancement of robust PCA 9th

引用

Joint IAPR 9th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2002 and 4th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2002

作者： Langs, Georg Bischof, Horst Kropatsch, Walter G. Pattern Recognition and Image Processing Group 183/2 Institute for Computer Aided Automation Vienna University of Technology Favoritenstr. 9 ViennaA-1040 Austria Institute for Computer Graphics and Vision TU Graz Inffeldgasse 16 2.OG GrazA-8010 Austria

ISBN: (纸本)3540440119

In this paper we deal with performance improvement of robust PCA algorithms by replacing regular subsampling of images by an irregular image pyramid adapted to the expected image content. The irregular pyramid is a structure built based on knowledge gained from the training set of images. It represents different regions of the image with different level of detail, depending on their importance for reconstruction. This strategy enables us to improve reconstruction results and therefore the recognition significantly. The training algorithm works on the data necessary to perform robust PCA and therefore requires no additional input. © Springer-Verlag Berlin Heidelberg 2002.

关键词： image enhancement

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