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检索条件"机构=Laboratory for Computer Vision and Image Processing"

共 343 条记录，以下是21-30 订阅

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Extraction of the superficial facial vasculature, vital signs waveforms and rates using thermal imaging

Extraction of the superficial facial vasculature, vital sign...

引用

2010 IEEE computer Society Conference on computer vision and Pattern Recognition - Workshops, CVPRW 2010

作者： Gault, Travis R. Blumenthal, Nicholas Farag, Aly A. Starr, Tom Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)9781424470297

This work deals with non-invasive and non-intrusive measurements of the human facial vasculature from thermal imaging, and estimates the waveforms and rates of the arterial pulse. The paper addresses the issues involved with use of Long-Wave IR imaging in studies of human biometrics, and focuses on measurements of human's heart rate based on a small number of thermal video frames. Infrared videos of 30 subjects were recorded at two distances. Vascular mapping and multi-resolution analysis are used to calculate a subject's heart rate using only 512 Long-Wave IR video frames (17.07 seconds). This semi-automatic process is typically 89-99% accurate, with average accuracies at both distances at approximately 93%. The work is a step in a comprehensive computer vision system for computational studies on humanmachine interface. © 2010 IEEE.

关键词： Infrared imaging

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Two Sequential Stages Classifier for Multispectral Data

Two Sequential Stages Classifier for Multispectral Data

引用

Conference on computer vision and Pattern Recognition Workshop, CVPRW 2003

作者： Mohamed, Refaat M. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville LouisvilleKY40292 United States

ISBN: (纸本)0769519008

In this paper, we present an approach for the classification of remote sensing multispectral data, which consists of two sequential stages. The first stage exploits the capabilities of the Support Vector Machines (SVM) approach for density estimation and uses it in a Bayes classification setup. In a typical image, the class of a pixel is highly dependent on the classes of its neighbor pixels. The second stage exploits the dependency of the classes. We incorporate this dependency using stochastic modeling of the context as a Markov Random Field (MRF). The MRF is modeled using Besag model and implemented using the Iterative Conditional Modes (ICM) algorithm. Results show that the stochastic modeling approach enhances the results and provides reasonable smoothness in the classified image. © 2003 IEEE.

关键词： Remote sensing

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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...

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 new unsupervised approach for the classification of multispectral data

A new unsupervised approach for the classification of multis...

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6th International Conference on Information Fusion, FUSION 2003

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

ISBN: (纸本)0972184449

In this paper, we present a new approach for unsupervised pixel-wise classification of multispectral data. In this approach, we estimate the number of classes in a data set as well as the parameters of each class. This approach doesn't require training samples. A scene is modeled as a realization of a random field formed of a mixture distribution. We employ an EM algorithm to estimate the parameters of this mixture. The algorithm iterates to estimate the proper number of classes that compose the scene, and also the parameters of these classes. Theoretically, the algorithm can be applied for arbitrary forms of distributions for the classes in the scene, either parametric or non parametric. This paper focuses on the parametric estimation case. The approach has been applied to synthetic and real world multispectral data and provided quite encouraging results compared to other classical classification approaches. © Commonwealth of Australia 2003.

关键词： Classification (of information)

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Multi-modal medical volumes fusion by surface matching 2nd

Multi-modal medical volumes fusion by surface matching

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2nd International Conference on Medical image Computing and computer-Assisted Intervention, MICCAI 1999

作者： Eldeib, Ayman M. Yamany, Sameh M. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville LouisvilleKY40292 United States

ISBN: (纸本)354066503X

This paper presents a fast, six degrees of freedom registration technique to accurately locate the position and orientation of medical volumes (obtained from CT/MRI scans for the same patient) with respect to each other. The main contribution of this work is the use of a novel surface registration technique followed by a volume registration approach. The advantage of this combination is to have an accurate alignment and to reduce the time needed for registration. The surface registration uses a new surface representation scheme that captures the curvature information and codes it into 2-D images. Matching these images enables the recovery of the transformation parameters. For the multi-modal volume registration, the maximization of Mutual Information (MI) is used as a matching criterion and is enhanced by a new genetic based search technique. The results demonstrate that the new two-stage registration technique presented in this paper is robust in terms of speed and accuracy and allows for completely automatic registration of multimodality medical volumes. © Springer-Verlag Berlin Heidelberg 1999.

关键词： Degrees of freedom (mechanics)

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HD2UB: A voice communication system for underground mine monitoring 5

HD2UB: A voice communication system for underground mine mon...

引用

5th International Conference on computer Engineering and Networks, CENet 2015

作者： Yang, Yupeng Li, Wenhui Li, Huiying Zhu, Jinlong College of Computer Science and Technology Computer Vision and Image Processing Laboratory Jilin University Changchun130012 China

The voice communication is an important application in WSNs. The weakness and limitations of the communication distance of traditional systems are the main challenge, especially in complex underground (UG) environment. We provide a voice communication system named HD2UB, which adopts CML's CMX618 for voice data collection and forward error correction coding, TI's CC2530 for ZigBee network formation and voice data transmission. We assess the system from the perspective of Point to Point (P2P) End to End(E2E) and energy. The result shows that the HD2UB ensures voice quality in complex ZigBee network with higher integration and lower power consumption when compared with the existed ZigBee voice system. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Zigbee

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Virtual forces for camera planning in smart vision systems

Virtual forces for camera planning in smart vision systems

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7th IEEE Workshop on Applications of computer vision, WACV 2005

作者： Farag, Aly A. Abdel-Hakim, Alaa E. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0769522718

In this paper, we present a novel and robust approach for camera planning in smart vision systems. The proposed approach uses virtual forces to adjust the camera parameters (pan, tilt, translation ... etc.) toward the most proper values with respect to the application. It employs the physical spring model to direct the motion of the camera toward its target. Our approach is a general framework and any vision system can be easily modeled to use it. This approach has several advantages over previous work in camera planning. It is portable, expandable, robust, and flexible. We present a case study of a two degree-of-freedom stereo vision system to test our approach. The results show the efficiency of our approach even with poor system initialization and its robustness against possible weakness in the auxiliary algorithms used.

关键词： Stereo vision

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Two-stage neural network for volume segmentation of medical images

Two-stage neural network for volume segmentation of medical ...

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1997 IEEE International Conference on Neural Networks (ICNN 97)

作者： Ahmed, MN Farag, AA Computer Vision and Image Processing Laboratory University of Louisville Department of Electrical Engineering Louisville KY 40292 United States

ISBN: (纸本)0780341236

In this paper, we present a new system to segment and label CT/MRI Brain slices using feature extraction and unsupervised clustering. In this technique, each voxel is assigned a feature pattern consisting of a scaled family of differential geometrical invariant features. The invariant feature pattern is then assigned to a specific region using a two-stage neural network system. The first stage is a self-organizing principal components analysis (SOPCA) network that is used to project the feature vector onto its leading principal axes found by using principal components analysis. This step provides an effective basis for feature extraction. The second stage consists of a self-organizing feature map (SOFM) which will automatically cluster the input vector into different regions. The optimum number of regions (clusters) is obtained by a model fitting approach. Finally, a 3D connected component labeling algorithm is applied to ensure region connectivity. Implementation and performance of this technique are presented. Compared to other approaches, the new system is more accurate in extracting 3D anatomical structures of the brain, and can be apdated to real-time imaging scenarios.

关键词： segmentation pattern analysis learning in vision

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Edge Detection Using Matched Filter 27

Edge Detection Using Matched Filter

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第27届中国控制与决策会议

作者： LUO Hai-bo JIAO An-bo XU Ling-yun SHAO Chun-yan Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Key Laboratory of Image Understanding and Computer Vision University of Chinese Academy of Sciences Key Laboratory of Image Understanding and Computer Vision Liaoning Province

ISBN: (纸本)9781479970186

For target tracking,automatic target recognition and detection applications,they value edge detection sensibility,precision and location accuracy rather than other *** at these three criterions,this paper presents an edge detection algorithm based on matched ***,a matched filter was designed by analyzing the edge model for natural image,then the edge response was computed using the designed matched filter;secondly,the lower and discontinuous filtered responses were further suppressed using a dedicated one-dimension filter;finally,the edge image was obtained by binarizing the edge response with a local adaptive *** results illustrate that the proposed algorithm has more improvement than the Sobel and Canny operators in detection sensibility,precision and location ***,the algorithm can be implemented with parallel pipeline using FPGA,so it is also rather suitable for real-time applications.

关键词： edge detection,matched filter,local adaptive threshold,real-time application,noise suppression

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