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检索条件"任意字段=1st IEEE Workshop on Variational and Level Set Methods in Computer Vision"

共 33 条记录，以下是21-30 订阅

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A self-referencing level-set method for image reconstruction from sparse Fourier samples

A self-referencing level-set method for image reconstruction...

引用

ieee workshop on variational and level set methods in computer vision, VLSM 2001

作者： Ye, Jong Chul Bresler, Y. Moulin, P. Coordinated Science Laboratory University of Illinois Urbana-ChampaignIL61801 United States

ISBN: (纸本)076951278X

We address image estimation from sparse Fourier samples. The problem is formulated as joint estimation of the supports of unknown sparse objects in the image, and pixel values on these supports. The domain and the pixel values are alternately estimated using the level-set method and the conjugate gradient method, respectively. Our level-set evolution shows a unique switching behavior, which stabilizes the level-set evolution. Furthermore, the trade-off between the stability and the speed of evolution can be easily controlled by the number of the conjugate gradient steps, hence removing the re-initialization steps in conventional level set approaches. © 2001 ieee.

关键词： Conjugate gradient method

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level set methods and the stereo problem 1st

引用

1st International Conference on Scale-Space Theory in computer vision (Scale-Space 97)

作者： Faugeras, O Keriven, R INRIA Sophia Antipolis France MIT AI Lab Cambridge MA 02139 USA ENPC CERMICS Noisy Le Grand France

ISBN: (纸本)3540631674

We present a novel geometric approach for solving the stereo problem for an arbitrary number of images (greater than or equal to 2). It is based upon the definition of a variational principle that must be satisfied by the surfaces of the objects in the scene and their images. The Euler-Lagrange equations which are deduced from the variational principle provide a set of PDE's which are used to deform an initial set of surfaces which then move towards the objects to be detected. The level set implementation of these PDE's potentially provides an efficient and robust way of achieving the surface evolution and to deal automatically with changes in the surface topology during the deformation, i.e. to deal with multiple objects. Results of a two dimensional implementation of our theory are presented on synthetic and real images.

关键词： Equations of motion

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Solving the Chan-Vese model by a multiphase level set algorithm based on the topological derivative

引用

1st International Conference on Scale Space and variational methods in computer vision

作者： He, Lin Osher, stanley Johann Radon Inst Computat & Appl Math A-4040 Linz Austria Univ Calif Los Angeles Dept Mat Los Angeles CA 90095 USA

ISBN: (纸本)9783540728221

In this work, we specifically solve the Chan-Vese active contour model by multiphase level set methods. We first develop a fast algorithm based on calculating the variational energy of the Chan-Vese model without the length term. We check whether the energy decreases or not when we move a point to another segmented region. Then we draw a connection between this algorithm and the topological derivative, a concept emerged from the shape optimization field. Furthermore, to include the length terra of the Chan-Vese model;we apply a preprocessing step on the image by using nonlinear diffusion. We show numerical experiments to demonstrate the efficiency and the robustness of our algorithm.

关键词： image segmentation level set methods Chan-Vese model topological derivative

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level set methods for watershed image segmentation

引用

1st International Conference on Scale Space and variational methods in computer vision

作者： Tai, Xue-Cheng Hodneland, Erlend Weickert, Joachim Bukoreshtliev, Nickolay V. Lundervold, Arvid Gerdes, Hans-Hermann Univ Bergen Dept Math Johannes Brusgate 12 Bergen Norway Univ Bergen Dept Biomed N-5009 Bergen Norway Univ Saarland Fac Math & Comp Sci D-66041 Saarbrucken Germany

ISBN: (纸本)9783540728221

In this work a marker-controlled and regularized watershed segmentation is proposed. Only a few previous studies address the task of regularizing the obtained watershed lines from the traditional marker-controlled watershed segmentation. In the present formulation, the topographical distance function is applied in a level set formulation to perform the segmentation, and the regularization is easily accomplished by regularizing the level set functions. Based on the well-known Four-Color theorem, a mathematical model is developed for the proposed ideas. With this model, it is possible to segment any 2D image with arbitrary number of phases with as few as one or two level set functions. The algorithm has been tested on real 2D fluorescence microscopy images displaying rat cancer cells, and the algorithm has also been compared to a standard watershed segmentation as it is implemented in MATLAB. For a fixed set of markers and a fixed set of challenging images, the comparison of these two methods shows that the present level set formulation performs better than a standard watershed segmentation.

关键词： Watersheds

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Detecting regions of dynamic texture

引用

1st International Conference on Scale Space and variational methods in computer vision

作者： Amiaz, Tomer Fazekas, Sandor Chetverikov, Dmitry Kiryati, Nahum Tel Aviv Univ Sch Elect Engn IL-69978 Tel Aviv Israel Comp & Automat Res Inst Budapest Hungary

ISBN: (纸本)9783540728221

Motion estimation is usually based on the brightness constancy assumption. This assumption holds well for rigid objects with a Lambertian surface, but it is less appropriate for fluid and gaseous materials. For these materials a variant of this assumption, which we call the brightness conservation assumption should be employed. Under this assumption an object's brightness can diffuse to its neighborhood. We propose a method for detecting regions of dynamic texture in image sequences. Segmentation into regions of static and dynamic texture is achieved by using a level set scheme. The level set function separates the images into areas obeying brightness constancy and those which obey brightness conservation. Experimental results on challenging image sequences demonstrate the success of the segmentation scheme and validate the model.

关键词： dynamic texture level set optical flow

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The variational origin of motion by Gaussian curvature

引用

1st International Conference on Scale Space and variational methods in computer vision

作者： Overgaard, Niels Chr. Solem, Jan Erik Malmo Univ Appl Math Grp Sch Technol & Society Malmo Sweden

ISBN: (纸本)9783540728221

A variational formulation of an image analysis problem has the nice feature that it is often easier to predict the effect of minimizing a certain energy functional than to interpret the corresponding Euler-Lagrange equations. For example, the equations of motion for an active contour usually contains a mean curvature term, which we know will regularizes the contour because mean curvature is the first variation of curve length, and shorter curves are typically smoother than longer ones. In some applications it may be worth considering Gaussian curvature as a regularizing term instead of mean curvature. The present paper provides a variational principle for this: We show that Gaussian curvature of a regular surface in three-dimensional Euclidean space is the first variation of an energy functional defined on the surface. Some properties of the corresponding motion by Gaussian curvature are pointed out, and a simple example is given, where minimization of this functional yields a nontrivial solution.

关键词： Total mean curvature Gaussian curvature gradient descent flow level set methods Euler characteristic

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A variational framework for adaptive satellite images segmentation

引用

1st International Conference on Scale Space and variational methods in computer vision

作者： Besbes, Olfa Belhadj, Ziad Boujemaa, Nozha INRIA Rocquencourt IMEDIA Project F-78153 Le Chesnay France URISA SUPCOM Ariana Tunisia

ISBN: (纸本)9783540728221

In this paper, we present an adaptive variational segmentation algorithm of spectral / texture regions in satellite images using level set. Satellite images contain both textured and non-textured regions, so for each region spectral and texture cues are integrated according to their discrimination power. Motivated by Fisher-Rao linear discriminant analysis;two region weights are defined to code respectively the relevance of spectral and texture cues. Therefore;regions with or without texture are processed in an unified framework. The obtained segmentation criterion is minimized via curves evolution within an explicit correspondence between the interiors of evolving curves and regions in the segmentation. The shape derivation principle is used to derive the system of coupled evolution equations in such a way that we consider the region weights and the statistical parameters variability. Experimental results on both natural and satellite images are shown.

关键词： Image segmentation

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Otolith image analysis by computer vision

Otolith image analysis by computer vision

引用

1st International Conference on Bio-Inspired Systems and Signal Processing

作者： Chessel, Anatole Fablet, Ronan Kervrann, Charles Cao, Frederic IFREMER/LASAA France IRISA/VISTA France

ISBN: (纸本)9789898111180

Otoliths are small stone located in fish inner ears and characterised by an accretionnary growth. They act as a biological archive and are of much use in marine biology and ecology. In this article a computer vision framework is presented which recover the successive shapes of the otolith and the significant ridges and valleys from a 2D grayscale image. Seeing vision processes as complex systems, an iterated process is presented using two perceptual information, contrast and good continuity. The successive concentric shapes of the otoliths are recovered as the level-sets of a dome shaped potential function, computed in a variational framework. Potential applications includes in particular fish age estimation, otoliths morphogenesis modelling, otolith proxy fusion.

关键词： computer vision otolith fish biology and ecology biological image analysis detection a contrario variational methods

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Pixel level image fusion based on ICA and wavelet transform

Pixel level image fusion based on ICA and wavelet transform

引用

1st Asian and Pacific Conference on Synthetic Aperture Radar Proceedings

作者： Li Maokuan Guan Jian Naval Aeronaut Engn Acad Yantai 264001 Shandong Peoples R China

ISBN: (纸本)9781424411870

Image fusion is the process of producing a single image from a set of input images with more complete information and has broad applications in many fields, such as computer vision, automatic object detection, image processing, and remote sensing. In this paper, a pixel level image fusion algorithm based on Independent Component Analysis (ICA) and wavelet transform is proposed Firstly, we use the 2D discrete wavelet transform in order to extract multiple subband images. and then apply ICA on the subband images to get ICA bases, at last fuse the image by the independent component bases. The results show that it gives promising results as compared to previous methods and performs considerably well across a variety of multi-sensor imaging data.

关键词： wavelet transform Independent Component Analysis (ICA) Image Fusion

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Parsing R-CNN for Instance-level Human Analysis 32

Parsing R-CNN for Instance-Level Human Analysis

引用

32nd ieee/CVF Conference on computer vision and Pattern Recognition (CVPR)

作者： Yang, Lu Song, Qing Wang, Zhihui Jiang, Ming Beijing Univ Posts & Telecommun Beijing Peoples R China WiWide Inc Beijing Peoples R China

ISBN: (纸本)9781728132938

Instance-level human analysis is common in real-life scenarios and has multiple manifestations, such as human part segmentation, dense pose estimation, human-object interactions, etc. Models need to distinguish different human instances in the image panel and learn rich features to represent the details of each instance. In this paper, we present an end-to-end pipeline for solving the instance-level human analysis, named Parsing R-CNN. It processes a set of human instances simultaneously through comprehensive considering the characteristics of region-based approach and the appearance of a human, thus allowing representing the details of instances. Parsing R-CNN is very flexible and efficient, which is applicable to many issues in human instance analysis. Our approach outperforms all state-of-the-art methods on CIHP (Crowd Instance-level Human Parsing), MHP v2.0 (Multi-Human Parsing) and DensePose-COCO datasets. Based on the proposed Parsing R-CNN, we reach the 1st place in the COCO 2018 Challenge DensePose Estimation task. Code and models are publicly available(1).

关键词： And Body Pose Categorization Deep Learning Face Gesture Grou Recognition: Detection Retrieval Segmentation

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