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Deformation modeling for robust 3D face matching

Deformation modeling for robust 3D face matching

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Lu, Xiaoguang Jain, Anil K. Dept. of Computer Science and Engineering Michigan State University East Lansing MI 48824

ISBN: (纸本)0769525970

Human face recognition based on 3D surface matching is promising for overcoming the limitations of current 2D image-based face recognition systems. The 3D shape is invariant to the pose and lighting changes, but not invariant to the non-rigid facial movement, such as expressions. Collecting and storing multiple templates for each subject in a large database (associated with various expressions) is not practical. We present a facial surface modeling and matching scheme to match 2.5D test scans in the presence of both non-rigid deformations and large pose changes (multiview) to a neutral expression 3D face model. A geodesic-based resampling approach is applied to extract landmarks for modeling facial surface deformations. We are able to synthesize the deformation learned from a small group of subjects (control group) onto a 3D neutral model (not in the control group), resulting in a deformed template. A personspecific (3D) deformable model is built for each subject in the gallery w.r.t. the control group by combining the templates with synthesized deformations. By fitting this generative deformable model to a test scan, the proposed approach is able to handle expressions and large pose changes simultaneously. Experimental results demonstrate that the proposed matching scheme based on deformation modeling improves the matching accuracy. © 2006 ieee.

关键词： Face recognition

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A new deformable model for boundary tracking in cardiac MRI and its application to the detection of intra-ventricular dyssynchrony

A new deformable model for boundary tracking in cardiac MRI ...

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Gotardo, Paulo F. U. Boyer, Kim L. Saltz, Joel Raman, Subha V. Dept. of Electrical and Computer Engineering Ohio State University Columbus OH Dept. of Biomedical Informatics Ohio State University Columbus OH

ISBN: (纸本)0769525970

We present a new deformable model technique following a snake-like approach and using a complex Fourier shape descriptors parameterization to efficiently formulate the forces that constrain contour deformation. The method was successfully applied to track the left ventricle's (LV) endocardial and epicardial boundaries in sequences of short-axis magnetic resonance images depicting complete cardiac cycles. The extracted shapes show the method's robustness to weak contrast, noisy edge maps and to papillary muscle anatomy. Our second contribution is a statistical pattern recognition approach for the detection of asynchronous activation of the LV walls. We applied our deformable model method to provide spatio-temporal characterizations of complete cardiac cycles and then designed a linear classifier using the popular combination of Principal Component Analysis and Linear Discriminant Analysis. From a database comprising 33 patients, our approach provided a correct classification performance of 90.9% showing its potential in providing improved dyssynchrony characterization as an adjunct to current criteria for selecting patients for therapy, which provided a classification accuracy of just 62.5% on the same database. © 2006 ieee.

关键词： Tracking (position)

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Multi-resolution spin-images

Multi-resolution spin-images

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Quynh Dinh, H. Kropac, Steven Department of Computer Science Stevens Institute of Technology

ISBN: (纸本)0769525970

Johnson and Hebert's spin-images have been applied to the registration of range images and object recognition with much success because they are rotation, scale, and pose invariant. In this paper we address two issues concerning spin-images, namely: (1) comparing uncompressed spin-images across large datasets is costly, and (2) a method to select the appropriate bin size and image width for spin-images is not clearly defined. Our solution to these issues is a multi-resolution method that generates a pyramid of spin-images by successively decreasing the spin-image size by powers of two. To efficiently correlate surface points, we compare spin-images in a low-to-high resolution manner. Once multi-resolution spin-images are generated for a given object, we have found that the different resolutions can also be used to compare objects that have differing or non-uniform point densities. To select the appropriate bin sizes for comparing such objects, we use the ratio of the average edge lengths of the objects. We also show preliminary results of using the pyramid to converge on the appropriate image width by traversing the pyramid in a low-to-high resolution manner looking for the highest resolution at which the fewest number of highly correlated points are found to match a given feature point. © 2006 ieee.

关键词： Image analysis

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Non-rigid metric shape and motion recovery from uncalibrated images using priors

Non-rigid metric shape and motion recovery from uncalibrated...

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Del Bue, Alessio Lladó, Xavier Agapito, Lourdes Department of Computer Science Queen Mary University of London Mile End Road London El 4NS United Kingdom

ISBN: (纸本)0769525970

In this paper we focus on the estimation of the 3D Euclidean shape and motion of a non-rigid object which is moving rigidly while deforming and is observed by a perspective camera. Our method exploits the fact that it is often a reasonable assumption that some of the points are deforming throughout the sequence while others remain rigid. First we use an automatic segmentation algorithm to identify the set of rigid points which in turn is used to estimate the internal camera calibration parameters and the overall rigid motion. Finally we formalise the problem of non-rigid shape estimation as a constrained non-linear minimization adding priors on the degree of deformability of each point. We perform experiments on synthetic and real data which show firstly that even when using a minimal set of rigid points it is possible to obtain reliable metric information and secondly that the shape priors help to disambiguate the contribution to the image motion caused by the deformation and the perspective distortion. © 2006 ieee.

关键词： Image processing

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How do movie viewers perceive scene structure from dynamic cues

How do movie viewers perceive scene structure from dynamic c...

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Cheong, Loong-Fah Xiang, Xu Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117576 Singapore

ISBN: (纸本)0769525970

Cinema viewed from a location other than a Canonical Viewing Point (CVP) presents distortions to the viewer in both its static and dynamic aspects. Past works have investigated mainly the static aspect of this problem and attempted to explain why viewers still seem to perceive the scene very well. The dynamic aspect of depth perception, which is known as structure from motion, and its possible distortion, have not been well investigated. In this paper, we derive the dynamic depth cues perceived by the viewer and use the so-called iso-distortion framework to understand its distortion. The result is that viewers seated at a reasonably central position experience a shift in the intrinsic parameters of their visual systems. Despite this shift, the key properties of the perceived depths remain largely the same, being determined in the main by the accuracy to which extrinsic motion parameters can be recovered. For a viewer seated at a non-central position and watching the movie screen with a slant angle, the view is related to the view at the CVP by a homography, resulting in various aberrations such as non-central projection. © 2006 ieee.

关键词： Image processing

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Fast variational segmentation using partial extremal initialization

Fast variational segmentation using partial extremal initial...

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Solem, Jan Erik Overgaard, Niels Chr. Persson, Markus Heyden, Anders Applied Mathematics Group School of Technology and Society Malmö University Sweden

ISBN: (纸本)0769525970

In this paper we consider region-based variational segmentation of two- and three-dimensional images by the minimization of functionals whose fidelity term is the quotient of two integrals. Users often refrain from quotient functional, even when they seem to be the most natural choice, probably because the corresponding gradient descent PDEs are non-local and hence require the computation of global properties. Here it is shown how this problem may be overcome by employing the structure of the Euler-Lagrange equation of the fidelity term to construct a good initialization for the gradient descent PDE, which will then converge rapidly to the desired (local) minimum. The initializer is found by making a one-dimensional search among the level sets of a function related to the fidelity term, picking the level set which minimizes the segmentation functional. This partial extremal initialization is tested on a medical segmentation problem with velocity- and intensity data from MR images. In this particular application, the partial extremal initialization speeds up the segmentation by two orders of magnitude compared to straightforward gradient descent. © 2006 ieee.

关键词： Image segmentation

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Real time localization and 3D reconstruction

Real time localization and 3D reconstruction

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Mouragnon, E. Lhuillier, M. Dhome, M. Dekeyser, F. Sayd, P. LASMEA UMR 6602 Université Biaise Pascal CNRS 63177 Aubière Cedex France Image and Embedded Computer Lab. CEA/LIST/DTSI/SARC 91191 Gif s/Yvette Cedex France

ISBN: (纸本)0769525970

In this paper we describe a method that estimates the motion of a calibrated camera (settled on an experimental vehicle) and the tridimensional geometry of the environment. The only data used is a video input. In fact, interest points are tracked and matched between frames at video rate. Robust estimates of the camera motion are computed in real-time, key-frames are selected and permit the features 3D reconstruction. The algorithm is particularly appropriate to the reconstruction of long images sequences thanks to the introduction of a fast and local bundle adjustment method that ensures both good accuracy and consistency of the estimated camera poses along the sequence. It also largely reduces computational complexity compared to a global bundle adjustment. Experiments on real data were carried out to evaluate speed and robustness of the method for a sequence of about one kilometer long. Results are also compared to the ground truth measured with a differential GPS. © 2006 ieee.

关键词： Image reconstruction

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Are two rotational flows sufficient to calibrate a smooth non-parametric sensor

Are two rotational flows sufficient to calibrate a smooth no...

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Grossmann, Etienne Lee, Eun-Joo Hislop, Peter Nistér, David Stewénius, Henrik Dept. IRO U. de Montréal Computer Science Dept. U. of Kentucky Dept. of Mathematics U. of Kentucky Center for Visualization U. of Kentucky

ISBN: (纸本)0769525970

We present an attempt to determine whether the shape of a generic central-projection camera, such as the eye of an insect or a log-polar camera, can be determined from two motion flows resulting from purely rotational motions with non-collinear axes. Our first contribution is to write the smooth non-parametric calibration problem as a differential equation. It is unclear at present whether this problem has unique solution, up to an orthogonal transformation. Our second contribution is a discretized version of this smooth problem, for which we give a calibration algorithm - a third contribution. Using this algorithm, we explore numerically the properties of the discrete self-calibration problem, giving some insight on the nature of the problem. We show examples of successful self-calibration, but cannot give a definite affirmative answer to the question in the title. © 2006 ieee.

关键词： Sensors

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Using multiple segmentations to discover objects and their extent in image collections

Using multiple segmentations to discover objects and their e...

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2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Russell, Bryan C. Efros, Alexei A. Sivic, Josef Freeman, William T. Zisserman, Andrew CS and AI Laboratory Massachusetts Institute of Technology Cambridge MA 02139 United States School of Computer Science Carnegie Mellon University Pittsburgh PA 15213 United States Dept. of Engineering Science University of Oxford Oxford OX1 3PJ United Kingdom

ISBN: (纸本)0769525970

Given a large dataset of images, we seek to automatically determine the visually similar object and scene classes together with their image segmentation. To achieve this we combine two ideas: (i) that a set of segmented objects can be partitioned into visual object classes using topic discovery models from statistical text analysis;and (ii) that visual object classes can be used to assess the accuracy of a segmentation. To tie these ideas together we compute multiple segmentations of each image and then: (i) learn the object classes;and (ii) choose the correct segmentations. We demonstrate that such an algorithm succeeds in automatically discovering many familiar objects in a variety of image datasets, including those from Caltech, MSRC and LabelMe. ©2006 ieee.

关键词： Image segmentation

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Selecting principal components in a two-stage LDA algorithm

Selecting principal components in a two-stage LDA algorithm

引用

2006 ieee computer society conference on computer vision and pattern recognition, CVPR 2006

作者： Zhu, Manli Martínez, Aleix M. Department of Electrical and Computer Engineering Ohio State University Columbus OH 43210

ISBN: (纸本)0769525970

Linear Discriminant Analysis (LDA) is a well-known and important tool in pattern recognition with potential applications in many areas of research. The most famous and used formulation of LDA is that given by the Fisher-Rao criterion, where the problem reduces to a simple simultaneous diagonalization of two symmetric, positive-definite matrices, A and B;i.e. B-1AV = VA. Here, A defines the metric to be maximized, while B defines the metric to be minimized. However, when B has near-zero eigenvalues, the Fisher-Rao criterion gets dominated by these. While this works well when such small variances describe vectors where most of the discriminant information is, the results will be incorrect when these small variances are caused by noise. Knowing which of these near-zero values are to be used and which need to be eliminated is a challenging yet fundamental task in LDA. This paper presents a criterion for the selection of those vectors of B that are best for classification. The proposed solution is based on a simple factorization of B-1 A that permits the re-ordering of the eigenvectors of B without the need to effect the end result. This allows us to readily eliminate the noisy vectors while keeping the most discriminant ones. A theoretical basis for these results is presented along with extensive experimental results to validate the claims. © 2006 ieee.

关键词： Principal component analysis

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