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

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Heat front propagation contours for 3D face recognition

Heat front propagation contours for 3D face recognition

引用

IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS)

作者： Mostafa Abdelrahman Aly A. Farag Moumen El-Melegy Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA University of Louisville Louisville KY US

Face recognition is a key biometric method aiming at identifying individuals by the features of face. Due to the challenges facing face recognition from 2D images, researchers have resorted to 3D face recognition. Our work in this paper is motivated by the recent and remarkable success of heat-based features for 3D object classification and retrieval. We propose an approach for 3D face recognition based on the front contours of heat propagation over the face surface. The front contours are extracted automatically as heat is propagating starting from a detected set of landmarks. The propagation contours are used to successfully discriminate the various faces. The proposed approach is evaluated on the largest publicly available database of 3D facial images and successfully compared to the state-of-the-art approaches in the literature.

关键词： Face Heating Three-dimensional displays Face recognition Mathematical model Kernel Equations

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A novel probabilistic simultaneous segmentation and registration using level set

A novel probabilistic simultaneous segmentation and registra...

引用

IEEE International Conference on image processing

作者： Melih S. Aslan Eslam Mostafa Hossam Abdelmunim Ahmed Shalaby Aly A. Farag Ben Arnold Computer Vision and Image Processing Lab. University of Louisville Louisville KY USA Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Computer and Systems Engineering Department Ain Shams University Cairo Egypt Image Analysis Inc. Columbia KY USA

We propose a new shape-based segmentation approach using the statistical shape prior and level sets method. The segmentation depends on the image information and shape prior. Training shapes are grouped to form a probabilistic model. The shape model is embedded into the image domain taking in consideration the evolution of a contour represented by a level set function. The evolution of the front gathers information from the image intensities and shape prior. The segmentation approach is applied in segmenting the vertebral bodies in CT images. Our results shows that the technique is accurate and robust compared with the other alternative in the literature.

关键词： Shape image segmentation Level set Computed tomography Accuracy Probabilistic logic

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Recognizing Rotated Faces from Two Orthogonal Views in Mugshot Databases

Recognizing Rotated Faces from Two Orthogonal Views in Mugsh...

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International Conference on Pattern Recognition

作者： Xiaozheng Zhang Yongsheng Gao Bai-ling Zhang Computer Vision & Image Processing Laboratory School of Engineering Griffith University Australia School of Computer Science and Mathematics Victoria University Australia

ISBN: (纸本)0769525210

Tolerance to pose variations is one of the key remaining problems in face recognition. It is of great interest in airport surveillance systems using mugshot databases to screen travellers' faces. This paper presents a novel pose-invariant face recognition approach using two orthogonal face images from mugshot databases. Virtual views under different poses are generated in two steps: shape modeling and texture synthesis. In the shape modeling step, a feature-based multilevel quadratic variation minimization approach is applied to generate smooth 3D face shapes. In the texture synthesis step, a non-Lambertian reflectance model is explored to synthesize facial textures taking into account both diffuse and specular reflections. A view-based face recognizer is used to examine the feasibility and effectiveness of the proposed pose-invariant face recognition. The experimental results show that the proposed method provides a new solution to the problem of recognizing rotated faces

关键词： Face recognition Shape Face detection Humans image databases computer vision Surveillance Spatial databases Reflectivity Reflection

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Effect of minicolumnar disturbance on dyslexic brains: an MRI study

Effect of minicolumnar disturbance on dyslexic brains: an MR...

引用

IEEE International Symposium on Biomedical Imaging

作者： N. El-Zehiry M. Casanova H. Hassan A. Farag Computer Vision and Image Processing Laboratory University of Louisville USA Department of Psychiatry and Behavioral Sciences University of Louisville USA

The minicolumn is generally considered the basic unit of the neocortex in all the mammalian brains. Enlargement of the cortical surface is believed to occur through the addition of minicolumns rather than a single neuron. This study aims at testing the hypothesis that brain developmental disorders can be diagnosed and analyzed in terms of the minicolumnar disturbance. To do this, we propose to correlate the pathological findings in terms of the minicolumnar structure to the MRI findings in terms of volumetric analysis

关键词： Magnetic resonance imaging Neurons Autism Pathology Aging computer vision image processing Psychiatry Testing Nerve fibers

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STATISTICAL MORPHABLE MODEL FOR HUMAN TEETH RESTORATION

STATISTICAL MORPHABLE MODEL FOR HUMAN TEETH RESTORATION

引用

IEEE International Conference on image processing

作者： Eslam Mostafa Shireen Elhabian Aly Abdelrahim Salwa Elshazly Aly Farag Computer Vision and Image Processing Laboratory University of Louisville KY USA Kentucky Imaging Technologies Louisville KY USA

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.

关键词： Teeth Shape Solid modeling Three-dimensional displays image restoration Dentistry Lighting

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image approximation and smoothing by support vector regression

Image approximation and smoothing by support vector regressi...

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International Joint Conference on Neural Networks (IJCNN)

作者： D. Kai Tik Chow Tong Lee Computer Vision and Image Processing Laboratory Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China

ISBN: (纸本)0780370449

A new image representation by support vector regression (SVR) is introduced. After a grey level image is approximated as a continuous function using SVR, which maps a 2D pixel coordinate input into a 1D pixel grey level output, the image can then be expressed in terms of the extracted support vectors and their corresponding Lagrange multipliers. The image is reconstructed by a linear combination of kernels with weights equal to the values of Lagrange multipliers. With support vector representation, we can observed that: 1) it is able to remove noise from image, the denoising effect of SVR representation is implicit during image encoding, and it can be controlled by the SVR training parameters; 2) if a Gaussian RBF kernel is used in SVR representation, Gaussian smoothing can be easily implemented by increasing the variance of kernel during image reconstruction and sharpening can be done by reducing the variance.

关键词： Smoothing methods Kernel Pixel Vectors Lagrangian functions image reconstruction Noise reduction image representation Gaussian noise image coding

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Automatic neural arbor reconstruction

Automatic neural arbor reconstruction

引用

IEEE Symposium on Nuclear Science (NSS/MIC)

作者： P.M. Gregson Computer Vision and Image Processing Laboratory Department of Electrical Engineering Technical University of Nova Scotia Halifax NS Canada

An algorithm for detecting neural processes in serial optical sections for use in an automated three-dimensional neural reconstruction system is presented. This parsimonious, nonlinear, psychophysically motivated algorithm addresses the problems specific to neural element detection and localization, viz., images with minimal resolution, operators with small spatial supports, highly curved, filamentous features, large variation in feature intensity profile, poor signal-to-noise ratio, and determination of depth without stereo. One first finds the magnitude and orientation of the maximum intensity second directional derivative. A family of curves is locally fitted to these data, and the projections of the data on the curve family are found. If a pixel lies on a curve with sufficient total projection, it is labeled with the magnitude, orientation, curvature, spatial extent, and element displacement. Depth is interpolated from the spatial extent data for corresponding neighborhoods in three adjacent (in depth) images by using an approximation to the depth-dependent optical point spread function. Experimental results using photomicrographs of cat visual cortex are presented.< >

关键词： image reconstruction computer vision Displays Spatial resolution Neural networks Nonlinear optics Optical interconnections Neurons image processing Laboratories

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A watermark for digital images

A watermark for digital images

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IEEE International Conference on image processing

作者： R.B. Wolfgang E.J. Delp Computer Vision and Image Processing Laboratory Purdue Multimedia Testbed Laboratory School of Electrical Engineering Purdue University West Lafayette IN USA

The growth of networked multimedia systems has magnified the need for image copyright protection. One approach used to address this problem is to add an invisible structure to an image that can be used to seal or mark it. These structures are known as digital watermarks. We describe two techniques for the invisible marking of images. We analyze the robustness of the watermarks with respect to linear and nonlinear filtering, and JPEG compression. The results show that our watermarks detect all but the most minute changes to the image.

关键词： Watermarking Digital images Multimedia systems Copyright protection Seals Robustness Nonlinear filters Filtering Transform coding image coding

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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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DEFORMABLE MODELS FOR RANDOM SMALL-SIZE OBJECTS: CASE OF LUNG NODULES IN CT TOMOGRAPHY

DEFORMABLE MODELS FOR RANDOM SMALL-SIZE OBJECTS: CASE OF LUN...

引用

IEEE International Conference on Acoustics, Speech and Signal processing

作者： Amal A. Farag James H. Graham Aly A. Farag Imaging Biomarkers and Computer-Aided Diagnosis Laboratory National Institutes of Health Bethesda MD Computer Vision and Image Processing Laboratory University of Louisville Louisville KY

ISBN: (纸本)9781479903573

Deformable models are common in image modeling and analysis. Random objects provide major challenges as shapes and appearances are hard to quantify;hence, formulation of deformable models are much harder to construct and validate. In this paper, we examine the effect of randomness on building the shape and appearance models for small-size lung nodules (< 1cm) which appear in computed tomography (CT) of the human chest. We devise an approach for annotation, which lends a standard mechanism for building traditional active appearance (AAM), active shape (ASM) and active tensor models (ATM). We illustrate the effectiveness of AAM for nodule detection.

关键词： CT ASM AAM Army Achievement Medal X-Ray Computed Tomography Deformable models computer aided software engineering Packaging Case Root nodules Shape Lung nodules Tomography ANNOTATIONS

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