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作者： Mostafa, Eslam Elhabian, Shireen Abdelrahim, Aly Elshazly, Salwa Farag, Aly Computer Vision and Image Processing Laboratory University of Louisville KY United States

ISBN: (纸本)9781479957514

While traditional dental fillings are molded during a dental visit, dental restoration (e.g. inlays and onlays) are fabricated in a dental lab to offer a long lasting reparative solution to tooth decay or similar structural damage. Such process requires dental technicians who are highly trained experts in tooth anatomy to pick an appropriate standard tooth model from a tooth database. The success of a restoration process primarily relies on the acquisition and modeling of an accurate 3D shape of the occlusal surface of interest for manufacturing purposes. Based on a single optical image, this paper provides an economical and automated solution for tooth restoration where user intervention is kept at the minimal. The inherit relation between the photometric information and the underlying 3D shape is formulated as a coupled statistical model where the effect of illumination is modeled using Spherical Harmonics. Moreover, shape and texture alignment is accomplished using a proposed definition of anatomical jaw landmarks which are automatically detected. The system is evaluated on database of 32 jaws for crown, inlay, and onlay restoration. Results shows a promising performance for using the proposed approach in clinical application. © 2014 IEEE.

关键词： Restoration

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image content-based active sensor planning for a mobile trinocular active vision system

Image content-based active sensor planning for a mobile trin...

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2004 International Conference on image processing, ICIP 2004

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

In this paper, we present a sensor planning approach for a mobile trinocular active vision system. At the stationary state (i.e., no motion) the sensor planning system calculates the generalized cameras' parameters (i.e., translational distance from the center, zoom, focus and vergence) using deterministic geometric specifications of both the sensors and the objects in their field of view. Some of these geometric parameters are difficult to be predetermined for the mobile system operation. In this paper, a new sensor planning approach, based on processing the content of the captured images, is proposed. The approach uses a combination of a closed-form solution for the translation between the three cameras, the vergence angle of the cameras as well as zoom and focus settings with the results of the correspondences between the acquired images and a predefined target object(s) obtained using the SIFT algorithm. We demonstrate the accuracy of the new approach using practical experiments. © 2004 IEEE.

关键词： image processing

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Probability density estimation by linear combinations of Gaussian kernels-generalizations and algorithmic evaluation

Probability density estimation by linear combinations of Gau...

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International Conference on Multimedia Technology

作者： Farag, Amal A. Ali, Asem M. Elhabian, Shireen Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY United States

ISBN: (纸本)9781612847740

This paper examines parametric density estimation using a variable weighted sum of Gaussian kernels, where the weights may take positive and negative values. Various statistical properties of the estimator are studied as well as its extensions to multidimensional probability density estimation. Identification of the estimator parameters are computed by a modified EM algorithm and the number of kernels are estimated by information theoretic approach, using the Akiake Information Criterion (AIC). This paper provides empirical evaluation of the estimator with respect to window-based estimators and the classical linear combinations of Gaussian estimator that uses only positive weights, showing its robustness (in terms of accuracy and speed) for various applications in image and signal analysis and machine learning. © 2011 IEEE.

关键词： Probability density function

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Frameworks for multimodal biometric using sparse coding

Frameworks for multimodal biometric using sparse coding

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3rd Sino-Foreign-Interchange Workshop on Intelligent Science and Intelligent Data Engineering, IScIDE 2012

作者： Huang, Zengxi Liu, Yiguang Huang, Ronggang Yang, Menglong Vision and Image Processing Laboratory College of Computer Science Sichuan University Chengdu China

ISBN: (纸本)9783642366680

In this paper, we will introduce three frameworks for multimodal biometric using sparse representation based classification (SRC), which has been successfully used in many classification tasks recently. The first framework is multimodal SRC at match score level (MSRC-s), in which feature of each modality is sparsely coded independently, and then their representation fidelities are used as match scores for multimodal classification. The other two frameworks are multimodal SRC at feature level (MSRC-f1, MSRC-f2), where features of all modalities are first fused and then classified by using SRC. The difference between them is that MSRC-f1 fuses the features to form a unique multimodal feature vector, while MSRC-f2 implicitly combines the features in an iterative joint sparse coding process. As a typical application, the fusion of face and ear for human identification is investigated by using the three frameworks. In our experiments, Principal Component Analysis (PCA) based feature extraction is applied. Many results demonstrate that the proposed multimodal methods are significantly better than the multimodal recognition using common classifiers. Among the SRC based methods, MSRC-s gets the top recognition accuracy in almost all the test items, which might benefit from allowing sparse coding independence for different modalities. © Springer-Verlag 2013.

关键词： Principal component analysis

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The cardeye: A trinocular active vision system 2

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2nd International Workshop on computer vision Systems, ICVS 2001

作者： Hemayed, Elsayed E. Ahmed, Moumen T. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville KY40292 United States

ISBN: (纸本)3540422854

The CardEye is an experimental, trinocular, 3D active vision system. Our goal is to create a flexible, precise tool for active vision research. The system uses an agile trinocular vision head that will be mounted on a robotic arm. The system has several degrees of freedom: pan, tilt, roll, vergence and variable baseline in addition to the automated zoom and focus of the cameras lenses. It utilizes an active lighting device to assist in the surface reconstruction process. After solving for the best system variables to image a surface, a novel multi-stage reconstruction algorithm is used to build a rich, complete 3D model of the surface. In this paper we describe the novel architecture of the system and its successful application to reconstruction of objects of varying surface characteristics. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Degrees of freedom (mechanics)

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Less is more: Cropping to improve facial recognition with thermal images

Less is more: Cropping to improve facial recognition with th...

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2nd International Conference on Multimedia Technology, ICMT 2011

作者： Gault, Travis R. Mostafa, Eslam Farag, Ahmed A. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY United States

ISBN: (纸本)9781612847740

Numerous studies have investigated the functionality of the human facial recognition mechanisms with aims to improve computer vision methodologies. Understanding these mechanisms is important for applications in computer vision, as one goal of researchers is to create automatic facial recognition systems to equal the robustness of the human facial recognition system. Work in the field of human facial recognition shows that humans are able to recognize faces under very challenging scenarios, including partial occlusion. However, most human facial recognition experiments are conducted in the visible and near-infrared spectrums. During human facial recognition experiments with thermal images conducted in the lab, we found that removing the lower face yields better recognition results than when using the entire face. These tests included standard facial recognition algorithms and the results showed Rank 1 Recognition improvements of 10-25%, depending on the amount of occlusion derived from certain anatomical landmarks. © 2011 IEEE.

关键词： computer vision

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Dynamic weighting of facial features for automatic pose-invariant face recognition

Dynamic weighting of facial features for automatic pose-inva...

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2012 9th Conference on computer and Robot vision, CRV 2012

作者： Mostafa, Eslam A. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY United States

ISBN: (纸本)9780769546834

This paper proposes an automatic pose-invariant face recognition system. In our approach, we consider the texture information around the facial features to compute the similarity measure between the probe and gallery images. The weight of each facial feature is dynamically estimated based on its robustness to the pose of the captured image. An approach to extract the 9 facial features used to initialize the Active shape model is proposed. The approach is not dependent on the texture around the facial feature only but incorporates the information obtained about the facial feature relations. Our face recognition system is tested on common datasets in pose evaluation CMU-PIE and FERET. The results show out-performance of the state of the art automatic face recognition systems. © 2012 IEEE.

关键词： Face recognition

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3D reconstruction of the human jaw: A new approach and improvements 4th

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4th International Conference on Medical image Computing and computer-Assisted Intervention, MICCAI 2001

作者： Ahmed, Moumen T. Eid, Ahmed H. Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville KY40292 United States

ISBN: (纸本)3540426973

This paper presents a new, practical approach for 3D reconstruction of the human jaw from a sequence of intra-oral images. This research has an immense value in various dental practices including implants, tooth alignment, and craniofacial surgery. Our approach is based on the recently-proposed space carving algorithm for shape recovery. This algorithm provides more flexibility to the reconstruction process and eliminates several constrains imposed by other traditional approaches such as stereo and shape from shading. Our experimental results have shown that the approach is able to reconstruct 3D models of the human jaw with sub-millimeter accuracy. © Springer-Verlag Berlin Heidelberg 2001.

关键词： image reconstruction

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Cerebrovascular segmentation for MRA data using level sets

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International Congress Series 2003年第C期1256卷 246-252页

作者： Hassan, Hossam Farag, Aly A Computer Vision Image Processing Laboratory University of Louisville Lutz Hall Louisville KY 40292 United States

In this paper, we use a level set based segmentation algorithm to extract the vascular tree from Phase Contrast Magnetic Resonance Angiography, “PCMRA”. Classification model finds an optimal partition of homogeneous classes with regular interfaces. Regions and their interfaces are represented by level set functions. The algorithm initializes level sets in each image slice using automatic seed initialization and then iteratively, each level set approaches the steady state and contains the vessel or non-vessel area. The results are validated using a phantom that simulates the “PCMRA”. The approach is fast and accurate. Results on various cases demonstrate the accuracy of the approach. © 2003, Elsevier Science B.V. All rights reserved.

关键词： Level set segmentation PCMRA PDE Seed initialization Vascular tree

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Parameter estimation in Gibbs-Markov image models

Parameter estimation in Gibbs-Markov image models

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6th International Conference on Information Fusion, FUSION 2003

作者： El-Baz, Ayman Farag, Aly A. Computer Vision and Image Processing Laboratory University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0972184449

This paper introduces two novel approaches to estimate the clique potentials in binary and multilevel realizations of Gibbs Markov random field (GMRF) models. The first approach employs a genetic algorithm (CA) in order to arrive at the closest synthesized image that resembles the original "observed" image. The Second approach is used to estimate the parameters of Gaussian Markov random field. Given an image formed of a number of classes, an initial class density is assumed and the parameters of the densities are estimated using the EM approach. Convergence to the true distribution is tested using the Levy distance. The segmentation of classes is performed iteratively using the ICM algorithm and a genetic algorithm (GA) search approach that provides the maximum a posteriori probability of pixel classification. During the iterations, the GA approach is used to select the clique potentials of the Gibbs-Markov models used for the observed image. The algorithm stops when a fitness function, equivalent to the maximum a posteriori probability, does not change. The approach has been tested on synthetic and real images and is shown to provide satisfactory results. © Commonwealth of Australia 2003.

关键词： Genetic algorithms

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