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A Unified Framework for Performance Evaluation of 3-D Reconstruction Techniques

A Unified Framework for Performance Evaluation of 3-D Recons...

引用

IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： A. Eid A. Farag Computer Vision and Image Processing (CVIP) Laboratory University of Louisville Louisville KY USA

In this paper we consider the problem of performance evaluation of 3-D reconstruction techniques from calibrated sequence of images. We propose a unified framework for the evaluation process assuming the existence of ground truth data collected by a 3-D laser scanner. Firstly, we propose a new pre-evaluation technique for 3-D data registration based on silhouettes alignment. The performance of this technique is independent of the output quality of the 3-D reconstruction technique under test. This is a major advantage of our technique since the quality issue, which is not guarantee under the evaluation topic, is a challenge for any 3-D registration technique. Secondly, we propose a geometrically based evaluation methodology. The method is based on the geometrical matching of uniformly distributed patches of both ground truth and under-test data sets. The method is insensitive to the relative density of data sets. In addition, it provides a method for localizing errors which is a crucial step for diagnosis and data fusion post-evaluation techniques. Finally, we provide experimental results on the evaluation of stereo and space carving techniques.

关键词： Three dimensional displays Stereo vision Testing computer vision Optical sensors Cameras image processing Laboratories Stereo image processing Fuses

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Shape Representation and Registration using Vector Distance Functions

Shape Representation and Registration using Vector Distance ...

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： Hossam Abd El Munim Aly A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

This paper introduces a new method for shape registration by matching vector distance functions. The vector distance function representation is more flexible than the conventional signed distance map since it enables us to better control the shapes registration process by using more general transformations. Based on this model, a variational frame work is proposed for the global and local registration of shapes which does not need any point correspondences. The optimization criterion can handle efficiently the estimation of the global registration parameters. A closed form solution is provided to handle an incremental free form deformation model for covering the local deformations. This is an advantage over the gradient descent optimization which is biased towards the initialization and is more time consuming. Results of real shapes registration will be demonstrated to show the efficiency of the proposed approach with small and large global/local deformations.

关键词： Shape measurement computer vision Shape control image segmentation Distortion measurement image processing Laboratories Closed-form solution Deformable models Biomedical imaging

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A silhouette-contour based 3-D registration methodology as a pre-evaluation step of 3-D reconstruction techniques

A silhouette-contour based 3-D registration methodology as a...

引用

IEEE International Conference on image processing

作者： A. Farag A. Eid Computer Vision and Image Processing (CVIP) Laboratory University of Louisville Louisville KY USA

Data registration is a crucial step in performance evaluation procedures that aim at localizing errors in given measured data. Under the performance evaluation topic, the probably corrupted measured data should be accurately registered/aligned to the ground truth data such that the registration process would not affect the accuracy of the consequent evaluation steps. To cope with this problem, another registration methodology that can go beyond the conventional ones should be used. Here we propose a novel approach for 3-D data registration. The performance of the approach is totally independent of the measured data set. The key advantage of this approach is that it keeps the registration process away from being affected by the probably corrupted data sets, hence it permits confidential evaluation results.

关键词： Three dimensional displays computer vision Iterative closest point algorithm Application software Iterative algorithms Calibration image processing Laboratories computer errors Object recognition

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Face recognition at-a-distance using texture, Sparse-Stereo, and Dense-Stereo

Face recognition at-a-distance using texture, Sparse-Stereo,...

引用

International Conference on Multimedia Technology

作者： Mostafa Abdelrahman Shireen Elhabian Asem Ali Aly A. Farag Computer Vision & Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

ISBN: (纸本)9781612847719

This paper proposes a framework for face recognition at a distance based on texture, Sparse-Stereo, and Dense-stereo reconstruction. We develop a 3D acquisition system that consists of two CCD stereo cameras mounted on pan-tilt units with adjustable baseline. In this paper we introduce our stereo-based indoor/outdoor environment and different ranges human faces database. Also, we propose a front-to-end system of 3D face reconstruction and recognition. We first detect the facial region and extract its landmark points, which are used to initialize the face alignment algorithm. The fitted mesh vertices, generated from the face alignment process, provide point correspondences between the left and right images of a stereo pair; stereo-based reconstruction is then used to infer the 3D information of the mesh vertices. Also the dense 3D is reconstructed for the cropped stereo pair based on graph cut approach. We perform experiments regarding the use of different features extracted from these vertices for face recognition. The cumulative rank curves (CMC), which are generated using the proposed framework, confirm the feasibility of the proposed work for long distance recognition of human faces.

关键词： Face Face recognition Three dimensional displays image color analysis Skin Feature extraction Databases

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Robust centerline extraction framework using level sets

Robust centerline extraction framework using level sets

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： M.S. Hassouna A.A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

In this paper, we present a novel framework for computing centerlines for both 2D and 3D shape analysis. The framework works as follows: an object centerline point is selected automatically as the point of global maximum Euclidean distance from the boundary, and is considered a point source (Ps) that transmits a wave front that evolves over time and traverses the object domain. The front propagates at each object point with a speed that is proportional to its Euclidean distance from the boundary. The motion of the front is governed by a nonlinear partial differential equation whose solution is computed efficiently using level set methods. Initially, the P/sub S/ transmits a moderate speed wave to explore the object domain and extract its topological information such as merging and extreme points. Then, it transmits a new front that is much faster at centerline points than non central ones. As a consequence, centerlines intersect the propagating fronts at those points of maximum positive curvature. Centerlines are computed by tracking them, starting from each topological point until the Ps is reached, by solving an ordinary differential equation using an efficient numerical scheme. The proposed method is computationally inexpensive, handles efficiently objects with complex topology, and computes centerlines that are centered, connected, one point thick, and less sensitive to boundary noise. In addition, the extracted paths form a tree graph without additional cost. We have extensively validated the robustness of the proposed method both quantitatively and qualitatively against several 2D and 3D shapes.

关键词： Robustness Level set Shape Euclidean distance Partial differential equations Data mining Merging Differential equations Topology Noise shaping

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Inpainting Large Missing Regions in Range images

Inpainting Large Missing Regions in Range Images

引用

International Conference on Pattern Recognition

作者： Arnav V Bhavsar A.N. Rajagopalan Image Processing and Computer Vision Laboratory Indian Institute of Technology Madras Chennai India

ISBN: (纸本)9781424475421

We propose a technique to in paint large missing regions in range images. Such a technique can be used to restore degraded/occluded range maps. It can also serve to reconstruct dense depth maps from sparse measurements which can speed up the acquisition. Our method uses the visual cue from segmentation of an intensity image registered to the range image. Our approach enforces that pixels in the same segment should have similar range. Our simple strategy involves plane-fitting and local medians over segments to compute local energies for labeling unknown pixels. Our results exhibit high quality in painting with very low errors.

关键词： Pixel image segmentation computer vision Pattern recognition Spatial resolution Bandwidth Conferences

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Level Set Segmentation Using Statistical Shape Priors

Level Set Segmentation Using Statistical Shape Priors

引用

IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： A.S. El-Baz A.A. Farag H.A. El Munim S.E. Yuksel Computer Vision & Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

A novel and robust 3-D segmentation approach is proposed using level sets based on shape constraints. The approach depends on both the gray level and shape information. A partial differential equation (PDE) is developed to control the evolution of the level sets. The PDE does not include weighting coefficients to be tuned, overcoming the disadvantages of other PDE approaches. The shape information is gathered from a set of the signed distance maps representing the training data as a histogram of the occurrences of the points inside and outside the object. We use a novel statistical approach to get a probability density function (pdf) for the signed distance map of the points inside and outside and also the distribution of gray level inside and outside the object. The proposed statistical approach is based on modelling the empirical density function (normalized histogram of occurrence) for either the gray level distribution or signed distance map with a linear combination of Gaussians (LCG) with positive and negative components. We modify an Expectation-Maximization (EM) algorithm to deal with the LCGs and also propose a novel EM-based sequential technique to get a close initial LCG approximation for the modified EM algorithm to start with. The pdf’s of the signed distance and intensity gray level are embedded in the speed function of the level set specifying the direction of evolution. Experimental results show how the approach is accurate in segmenting different types of 2-D and 3-D data sets including medical images.

关键词： Level set Shape Histograms Approximation algorithms Robustness Partial differential equations Training data Probability density function Density functional theory Gaussian distribution

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Shape from Shading for Hybrid Surfaces

Shape from Shading for Hybrid Surfaces

引用

IEEE International Conference on image processing

作者： Abdelrehim Ahmed Aly Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

This paper presents a new method for recovering the shape of hybrid surfaces that have both diffuse reflection and specular reflection using shape from shading (SFS). The image irradiance equation has been derived as an explicit partial differential equation (PDE) under the assumptions of orthographic camera projection and distant point light source. The reflectance model of Ward has been used to express the hybrid reflection as a linear combination from the diffuse and specular components. The resulting PDE is solved using the Lax-Friedrichs sweeping method. The proposed algorithm is evaluated by using both synthetic data and real images and the experimental results show the efficiency of the approach.

关键词： Shape Reflectivity Optical reflection Nonlinear equations Light sources Laboratories Layout Partial differential equations Brightness computer vision

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3-D reconstruction of the human jaw using space carving

3-D reconstruction of the human jaw using space carving

引用

IEEE International Conference on image processing

作者： M.T. Ahmed A.H. Eid A.A. Farag Computer Vision and Image Processing (CVIP) Laboratory University of Louisville Louisville KY USA

This paper presents a model-based vision system for dentistry that will assist in diagnosis, treatment planning and surgical simulation. Dentistry requires an accurate 3D representation of the teeth and jaws for diagnostic and treatment purposes. The proposed integrated computer vision system constructs a 3D model of the patient's dental occlusion using an intra-oral video camera. The space carving algorithm is used to reconstruct the shape of the human jaw. This algorithm provides more flexibility and eliminates several constraints imposed by other approaches like stereo. The system performance is investigated, and the results show acceptable reconstruction accuracy.

关键词： Three dimensional displays Humans Dentistry Machine vision Surgery Computational modeling Teeth computer vision Cameras Shape

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CSIFT: A SIFT Descriptor with Color Invariant Characteristics

CSIFT: A SIFT Descriptor with Color Invariant Characteristic...

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： A.E. Abdel-Hakim A.A. Farag Computer Vision and Image Processing Laboratory (CVIP) University of Louisville Louisville KY USA

SIFT has been proven to be the most robust local invariant feature descriptor. SIFT is designed mainly for gray images. However, color provides valuable information in object description and matching tasks. Many objects can be misclassified if their color contents are ignored. This paper addresses this problem and proposes a novel colored local invariant feature descriptor. Instead of using the gray space to represent the input image, the proposed approach builds the SIFT descriptors in a color invariant space. The built Colored SIFT (CSIFT) is more robust than the conventional SIFT with respect to color and photometrical variations. The evaluation results support the potential of the proposed approach.

关键词： Colored noise Robustness Histograms Photometry Feature extraction Lighting computer vision image retrieval image processing Laboratories

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