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Strings: variational deformable models of multivariate continuous boundary features

ieee TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2003年第11期25卷 1399-1410页

作者： Ghebreab, S Smeulders, AWM Univ Amsterdam Inst Informat Intelligent Sensory Informat Syst Grp Amsterdam Netherlands

We propose a new image segmentation technique called strings. A string is a variational deformable model that is learned from a collection of example objects rather than built from a priori analytical or geometrical knowledge. As opposed to existing approaches, an object boundary is represented by a one-dimensional multivariate curve in functional space, a feature function, rather than by a point in vector space. In the learning phase, feature functions are defined by extraction of multiple shape and image features along continuous object boundaries in a given learning set. The feature functions are aligned, then subjected to functional principal components analysis and functional principal regression to summarize the feature space and to model its content, respectively. Also, a Mahalanobis distance model is constructed for evaluation of boundaries in terms of their feature functions, taking into account the natural variations seen in the learning set. In the segmentation phase, an object boundary in a new image is searched for with help of a curve. The curve gives rise to a feature function, a string, that is weighted by the regression model and evaluated by the Mahalanobis model. The curve is deformed in an iterative procedure to produce feature functions with minimal Mahalanobis distance. Strings have been compared with active shape models on 145 vertebra images, showing that strings produce better results when initialized close to the target boundary, and comparable results otherwise.

关键词： machine learning deformable models energy minimization multivariate statistics shape analysis functional data analysis chemometrics active shape models

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Stereoscopic shading: Integrating multi-frame shape cues in a variational framework

Stereoscopic shading: Integrating multi-frame shape cues in ...

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ieee Conference on computer vision and Pattern Recognition (CVPR 2000)

作者： Jin, HL Yezzi, A Soatto, S Washington Univ St Louis MO 63130 USA

ISBN: (纸本)0769506623

We address the problem of integrating multi-frame stereo and shading cues within the framework of optimization in the infinite-dimensional space of piecewise smooth surfaces. Cue integration then reduces to the determination of regions where prior assumptions on the reflectance of the surfaces can be enforced. By combining cues, our formulation allows defining a well-posed problem even when reconstruction from stereo or shading in isolation would be ill-posed. For a simplified model we prove the necessary conditions for optimality, and propose an iterative optimization algorithm, which we implement using ultra-narrowband level set methods.

关键词： Stereo vision

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Two variational models for multispectral image classification 3rd

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3rd International workshop on Energy Minimization methods in computer vision and Pattern Recognition

作者： Samson, C Blanc-Féraud, L Aubert, G Zerubia, J UNSA CNRS Ariana Joint Res Grp 13S F-06902 Sophia Antipolis France INRIA F-06902 Sophia Antipolis France Univ Nice CNRS UMR 6621 Lab JA Dieudonne F-06108 Nice 2 France

ISBN: (纸本)3540425233

We propose two variational models for supervised classification of multispectral data. Both models take into account contour and region information by minimizing a functional compound of a data term (2D surface integral) taking into account the observation data and knowledge on the classes, and a regularization term (1D length integral) minimizing the length of the interfaces between regions. This is a free discontinuity problem and we have proposed two different ways to reach such a minimum, one using a Gamma-convergence approach and the other using a level set approach to model contours and regions. Both methods have been previously developed in the case of monospectral observations. Multispectral techniques allow to take into account information of several spectral bands of satellite or aerial sensors. The goal of this paper is to present the extension of both variational classification methods to multispectral data. We show an application on real data from SPOT (XS mode) satellite for which we have a ground truth. Our results are also compared to results obtained by using a hierarchical stochastic model.

关键词： classification multispectral images Gamma-convergence level-set methods active regions active contours

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Threshold-based 3D tumor segmentation using level set (TSL)

Threshold-based 3D tumor segmentation using level set (TSL)

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7th ieee workshop on Applications of computer vision, WACV 2007

作者： Taheri, Sima Ong, Sim Heng Chong, Vincent Department of Electrical and Computer Engineering National University of Singapore Department of Diagnostic Radiology National University of Singapore

ISBN: (纸本)0769527949

Three-dimensional segmentation is reliable approach to achieve a proper estimation of tumor volume. Among all possible methods for this purpose, level set can be used as a powerful tool which implicitly extracts the tumor surface. In this paper, we introduce a threshold-based algorithm for 3D tumor segmentation using level set (TSL). This algorithm uses a global threshold to form the level set speed function which is updated iteratively throughout the level set growing process. An important feature of TSL is that no explicit knowledge about the tumor and non-tumor density functions is required. The proposed method can be implemented in the automatic and semi-automatic forms depending on the complexity of the tumor shape. TSL is examined on several clinical MRIs for both visual and quantitative evaluation. Experimental results demonstrate the effectiveness of our approach. © 2007 ieee.

关键词： Image segmentation

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KillingFusion: Non-rigid 3D Reconstruction without Correspondences 30

KillingFusion: Non-rigid 3D Reconstruction without Correspon...

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30th ieee/CVF Conference on computer vision and Pattern Recognition (CVPR)

作者： Slavcheva, Miroslava Baust, Maximilian Cremers, Daniel Ilic, Slobodan Tech Univ Munich Munich Germany Siemens Corp Technol Munich Germany

ISBN: (纸本)9781538604571

We introduce a geometry-driven approach for real-time 3D reconstruction of deforming surfaces from a single RGB-D stream without any templates or shape priors. To this end, we tackle the problem of non-rigid registration by level set evolution without explicit correspondence search. Given a pair of signed distance fields (SDFs) representing the shapes of interest, we estimate a dense deformation field that aligns them. It is defined as a displacement vector field of the same resolution as the SDFs and is determined iteratively via variational minimization. To ensure it generates plausible shapes, we propose a novel regularizer that imposes local rigidity by requiring the deformation to be a smooth and approximately Killing vector field, i.e. generating nearly isometric motions. Moreover, we enforce that the level set property of unity gradient magnitude is preserved over iterations. As a result, KillingFusion reliably reconstructs objects that are undergoing topological changes and fast inter-frame motion. In addition to incrementally building a model from scratch, our system can also deform complete surfaces. We demonstrate these capabilities on several public datasets and introduce our own sequences that permit both qualitative and quantitative comparison to related approaches.

关键词： three-dimensional displays Vector field Correspondence deformation level set iterative methods jigs(templates)

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Shape prior segmentation of multiple objects with graph cuts

Shape prior segmentation of multiple objects with graph cuts

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ieee Conference on computer vision and Pattern Recognition

作者： Vu, Nhat Manjunath, B. S. Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

ISBN: (纸本)9781424422425

We present a new shape prior segmentation method using graph cuts capable of segmenting multiple objects. The shape prior energy is based on a shape distance popular with level set approaches. We also present a multiphase graph cut framework to simultaneously segment multiple, possibly overlapping objects. The multiphase formulation differs from multiway cuts in that the former can account for object overlaps by allowing a pixel to have multiple labels. We then extend the shape prior energy to encompass multiple shape priors. Unlike variational methods, a major advantage of our approach is that the segmentation energy is minimized directly without having to compute its gradient, which can be a cumbersome task and often relies on approximations. Experiments demonstrate that our algorithm can cope with image noise and clutter, as well as partial occlusions and affine transformations of the shape.

关键词： Graphic methods

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A bias correction variational level set image segmentation model combining structure extraction 2

A bias correction variational level set image segmentation m...

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2nd International Conference on Image, vision and Computing, ICIVC 2017

作者： Xili, Wang Li, Hu Xiyuan, Wang School of Computer Science Shaanxi Normal University Xi'an China School of Physics and Electronic Electrical Engineering Ningxia University Yinchuan China

ISBN: (纸本)9781509062379

The authors propose a variational level set image segmentation method for intensity inhomogeneous texture image. The method first extracts the main image structure by a relative total variation image decomposition method, which can better decompose the image into structural and textural parts. Then only uses the structural part as the input image for the variational level set segmentation. The intensity bias are estimated simultaneously in the level set curve evolution procedure. And the intensity inhomogeneity is solved by bias correction. The experiments indicate that the proposed method can remove texture, retain and smooth the structure information, estimate and correct intensity bias effectively. Thus, it improves the segmentation results compared with the level set image segmentation methods that take no account of intensity inhomogeneity and texture in images. © 2017 ieee.

关键词： Image segmentation

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Regularization of mappings between implicit manifolds of arbitrary dimension and codimension

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3rd International workshop on variational, Geometric, and level set methods in computer vision, VLSM 2005

作者： Shafrir, David Sochen, Nir A. Deriche, Rachid University of Tel-Aviv Ramat-Aviv Tel-Aviv 69978 Israel Odysee Project INRIA Sophia-Antipolis 2004 Route des Lucioles 06902 Sophia-Antipolis Cedex France

ISBN: (纸本)3540293485

We study in this paper the problem of regularization of mappings between manifolds of arbitrary dimension and codimension using variational methods. This is of interest in various applications such as diffusion tensor imaging and EEG processing on the cortex. We consider the cases where the source and target manifold are represented implicitly, using multiple level set functions, or explicitly, as functions of the spatial coordinates. We derive the general implicit differential operators, and show how they can be used to generalize previous results concerning the Beltrami flow and other similar flows. As examples, We show how these results can be used to regularize gray level and color images on manifolds, and to regularize tangent vector fields and direction fields on manifolds. © Springer-Verlag Berlin Heidelberg 2005.

关键词： variational techniques

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SEGMENTATION OF THE PROSTATE GLAND IN IMAGES USING PRIOR KNOWLEDGE AND level set METHOD 13

SEGMENTATION OF THE PROSTATE GLAND IN IMAGES USING PRIOR KNO...

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2017 workshop of computer vision (WVC)

作者： Sguario Coelho de Andrade, Mauren Louise Skeika, Everton Kaminski Aires, Simone Bello Univ Tecnol Fed Parana DAINF Dept Acad Informat Ponta Grossa Brazil

ISBN: (纸本)9781538614518

The treatment of prostate cancer is a great challenge, with very precise indications due to the high morbidity and mortality rates. Magnetic resonance imaging (MRI) is used to monitor the disease, providing a noninvasive clinical diagnosis to the patient. In this sense, this work proposes a segmentation of magnetic resonance imaging in models to identify a prostatic area, delimiting its area. To do so, a new approach to segmenting base images into a priori knowledge of the form and method level set will be developed. The performance of the proposed segmentation algorithm was evaluated with respect to the manual segmentation ground truth, active shape model and the level set method without priori knowledge. The experimental results obtained show that the inclusion of a priori information and the constraint imposed by the shape model contribute to greater segmentation accuracy than other methods.

关键词： Levet set image segmentation prior knowledge

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Visibility constrained surface evolution

Visibility constrained surface evolution

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2005 ieee computer Society Conference on computer vision and Pattern Recognition, CVPR 2005

作者： Solem, Jan Erik Kahl, Fredrik Heyden, Anders Applied Mathematics Group School of Technology and Society Malmö University Sweden Dept. of Computer Science and Engineering University of California San Diego San Diego CA United States

ISBN: (纸本)0769523722

The problem of feature-based surface reconstruction is considered in this paper. Our main contribution is the ability to handle visibility constraints, obtained from the projections of points, curves and silhouettes, in the surface fitting process. While traditional methods often ignore such information, we show that visibility constraints not only give better initial surface estimates and faster convergence, but also provide an important cue for determining surface topology. The problem is cast as a variational problem with constraints within the level set framework. It is shown how to evolve the surface without violating the visibility constraints using methods from variational calculus. Applications of the theory are detailed for a number of important cases of geometric primitives: points, curves and visual hulls. Several experiments on real image sequences are given to demonstrate the performance of the approach.

关键词： Image reconstruction

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