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Navier-stokes, fluid dynamics, and image and video inpainting

Navier-stokes, fluid dynamics, and image and video inpaintin...

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conference on computer Vision and pattern recognition (CVPR)

作者： M. Bertalmio A.L. Bertozzi G. Sapiro Computer Engineering Department University of Pompeu-Fabra Barcelona Spain Mathematics Department Duke University Durham NC USA Electrical & Computer Engineering Department University of Minnesota Minneapolis MN USA

ISBN: (纸本)0769512720

image inpainting involves filling in part of an image or video using information from the surrounding area. Applications include the restoration of damaged photographs and movies and the removal of selected objects. We introduce a class of automated methods for digital inpainting. The approach uses ideas from classical fluid dynamics to propagate isophote lines continuously from the exterior into the region to be inpainted. The main idea is to think of the image intensity as a 'stream function for a two-dimensional incompressible flow. The Laplacian of the image intensity plays the role of the vorticity of the fluid; it is transported into the region to be inpainted by a vector field defined by the stream function. The resulting algorithm is designed to continue isophotes while matching gradient vectors at the boundary of the inpainting region. The method is directly based on the Navier-Stokes equations for fluid dynamics, which has the immediate advantage of well-developed theoretical and numerical results. This is a new approach for introducing ideas from computational fluid dynamics into problems in computer vision and image analysis.

关键词： Fluid dynamics Streaming media Filling image restoration Motion pictures Laplace equations Algorithm design and analysis Navier-Stokes equations Computational fluid dynamics computer vision

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Three-dimensional medial shape representation incorporating object variability

Three-dimensional medial shape representation incorporating ...

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conference on computer Vision and pattern recognition (CVPR)

作者： M. Styner G. Gerig Department of Computer Science University of North Carolina Chapel Hill NC USA

ISBN: (纸本)0769512720

The paper presents a novel processing.scheme for the automatic computation of a medial shape model which is representative for an object population with shape variability. The sensitivity of medial descriptions to object variations and small boundary perturbations are fundamental problems of any skeletonization technique. These problems are approached with the computation of a model with common medial branching topology and grid sampling. This model is then used for a medial shape description of individual objects via a constrained model fit. The process starts from parametric 3D boundary representations with existing point-to-point homology between objects. The Voronoi diagram of each sampled object boundary is grouped into medial sheets and simplified by a pruning algorithm using a volumetric contribution criterion. Medial sheets are combined to form a common medial branching topology. Finally, the medial sheets are sampled and represented as meshes of medial primitives. We present new results on populations of up to 184 biological objects. For these objects, the common medial branching topology is described by a small number of sheets. Despite the coarse medial sampling, a close approximation of individual objects is achieved.

关键词： Shape Topology Sampling methods Data mining Skeleton computer science Grid computing Computational modeling image sampling computer vision

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Robust point feature matching in projective space

Robust point feature matching in projective space

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conference on computer Vision and pattern recognition (CVPR)

作者： G.Q. Chen Human Computer Interface Laboratories STMicroelectronics Inc. San Diego CA USA

ISBN: (纸本)0769512720

We present a robust method for matching point features across a set of images under full perspective projection. An expectation-maximization-like algorithm is developed to build an optimal potential match set (PMS) between each consecutive pair of views, by iteratively maximizing a heuristic objective function. All two-view matches are combined to form an M-view potential match set (MPMS) with a low contamination rate. Outliers in MPMS are removed incorporating the least-median-of-squares technique with projective reconstruction. The current work extends previous ones in two- or three-view matching, or under affine camera projection. Results on real imagery demonstrate the validity of the proposed method.

关键词： Robustness Cameras computer vision image edge detection Detectors Tracking Least squares approximation Laboratories Iterative algorithms Contamination

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Binding and segmentation of visual images by means of oscillatory neurons

Binding and segmentation of visual images by means of oscill...

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Annual International conference of the ieee Engineering in Medicine and Biology society (EMBC)

作者： M. Ursino G.E. La Cara A. Sarti Electronics University of Bologna Bologna Italy Computer Science and Systems University of Bologna Bologna Italy

A neural network based on Wilson-Cowan oscillators is used to perform object recognition in a two-dimensional visual scene. The temporal correlation among groups of oscillating neurons is used as the main criterion to solve the classic binding and segmentation problem. The network uses an original pattern of short-range lateral excitations among adjacent neurons to achieve the binding problem, and an external inhibitory global neuron to provide segmentation of multiple objects in the same visual scene. The latter may represent an "attention mechanism" from neurons at a higher hierarchical level. Simulations performed by using multiple idealized figures (up to 4-5) in the presence of noise suggest that the network can satisfactorily recognize objects in most cases. However, the threshold and time constant of the attention mechanism depend on the complexity (number of objects and level of noise) of the scene under examination. The present results may be useful to improve our understanding of how distributed activities are integrated in the neural system to form single object perceptions. In perspective, the proposed model may find in practical algorithms for object recognition.

关键词： image segmentation Neurons Layout Object recognition Oscillators computer science Neural networks Biological neural networks Algorithm design and analysis Feedback loop

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Learned templates for feature extraction in fingerprint images

Learned templates for feature extraction in fingerprint imag...

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conference on computer Vision and pattern recognition (CVPR)

作者： B. Bhanu Xuejun Tan Center for Research in Intelligent Systems University of California Riverside CA USA

ISBN: (纸本)0769512720

Most current techniques for minutiae extraction in fingerprint images utilize complex preprocessing.and postprocessing. In this paper, we propose a new technique, based on the use of learned templates, which statistically characterize the minutiae. Templates are teamed from examples by optimizing a criterion function using Lagrange's method. To detect the presence of minutiae in test images, templates are applied with appropriate orientations to the binary image only at selected potential minutia locations. Several performance measures, which evaluate the quality and quantity of extracted features and their impact on identification, are used to evaluate the significance of learned templates. The performance of the proposed approach is evaluated on two sets of fingerprint images: one is collected by an optical scanner and the other one is chosen from NIST special fingerprint database 4. The experimental results show that learned templates can improve both the features and the performance of the identification system.

关键词： Feature extraction Fingerprint recognition image matching Data mining Lagrangian functions Bifurcation Purification Filters Intelligent systems Optimization methods

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Articulated body posture estimation from multi-camera voxel data

Articulated body posture estimation from multi-camera voxel ...

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conference on computer Vision and pattern recognition (CVPR)

作者： I. Mikic M. Trivedi E. Hunter P. Cosman Computer Vision and Robotics Research Laboratory Department of Electrical and Computer Engineering University of California La Jolla CA USA

ISBN: (纸本)0769512720

We present a framework for articulated body model acquisition and tracking from voxel data. A 3D voxel reconstruction of the person's body is computed from silhouettes extracted from four cameras. The model acquisition process is fully automated. In the first frame, body parts are located sequentially. The head is located first, since its shape and size are unique and stable. Other parts are found by sequential template growing and fitting. This initial estimate of body part locations, sizes and orientations is then used as a measurement for the extended Kalman filter which ensures a valid articulated body model. The same filter, with a slightly modified state and state transition matrix, is then used for tracking. The performance of the system has been evaluated on several video sequences with promising results.

关键词： Cameras image reconstruction Biological system modeling Data mining computer vision Robot vision systems Head Shape Filters image segmentation

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Issues on the geometry of central catadioptric image formation

Issues on the geometry of central catadioptric image formati...

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conference on computer Vision and pattern recognition (CVPR)

作者： J.P. Barreto H. Araujo Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra Portugal

ISBN: (纸本)0769512720

An imaging system with a single effective viewpoint is called a central projection system. The conventional perspective camera is an example of a central projection system. Systems using mirrors to enhance the field of view while keeping a unique center of projection are also examples of central projection systems. Perspective image formation can be described by a linear model with well known properties. In general central catadioptric imaging, the mapping between points in the world and in the image is highly nonlinear. The paper establishes a general model for central catadioptric image formation made up of three functions: a linear function mapping the world into an oriented projective plane, a nonlinear transformation between two oriented projective planes, and a collineation in the plane. The model is used to study issues in the projection of lines. The equations and geometric properties of general catadioptric imaging of lines are derived. The application of the results in auto-calibration of central catadioptric systems and reconstruction are discussed. A method to calibrate the system using three line images is presented.

关键词： Cameras Mirrors Nonlinear equations Application software Data mining Computational geometry Robot vision systems computer vision Surveillance Virtual reality

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Neural mechanisms of bottom-up selection during visual search

Neural mechanisms of bottom-up selection during visual searc...

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Annual International conference of the ieee Engineering in Medicine and Biology society (EMBC)

作者： K.G. Thompson Laboratory of Sensorimotor Research National Eye Institute National Institutes of Health DHHS Bethesda MD USA

Models of attention and saccade target selection propose that within the brain there is a topographic map of visual salience that selects, through a winner-take-all mechanism, locations for further processing. The results of a series of recent experiments in monkeys performing pop-out visual search tasks suggest that the frontal eye field (FEF) functions as a map of visual salience. FEF is located at the interface of sensory and motor processing.and participates in the transformation of visual information into a command to move the eyes. Visually responsive neurons in FEF identify conspicuous objects in a search array regardless of the feature that renders conspicuousness. Furthermore, selection occurs at a constant interval following search array presentation and is dissociated from saccade production. The finding of a visual salience map in FEF validates models of visual selection and can serve to guide future empirical and theoretical investigations.

关键词： Neurons Brain modeling Eyes Kirk field collapse effect Laboratories Rendering (computer graphics) Production Retina Layout image converters

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Constructing facial identity surfaces in a nonlinear discriminating space

Constructing facial identity surfaces in a nonlinear discrim...

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conference on computer Vision and pattern recognition (CVPR)

作者： Yongmin Li Shaogang Gong H. Liddell Department of Computer Science Queen''s Mary University of London London UK

ISBN: (纸本)0769512720

Recognising face with large pose variation is more challenging than that in a fixed view, e.g. frontal-view, due to the severe non-linearity caused by rotation in depth, self-shading and self-occlusion. To address this problem, a multi-view dynamic face model is designed to extract the shape-and-pose-free facial texture patterns from multi-view face images. Kernel Discriminant Analysis is developed to extract the significant non-linear discriminating features which maximise the between-class variance and minimise the within-class variance. By using the kernel technique, this process is equivalent to a Linear Discriminant Analysis in a high-dimensional feature space which can be solved conveniently. The identity surfaces are then constructed from these non-linear discriminating features. Face recognition can be performed dynamically from an image sequence by matching an object trajectory and model trajectories on the identity surfaces.

关键词： Face recognition Face detection Kernel Linear discriminant analysis Principal component analysis Facial animation Analysis of variance computer vision Active shape model Active appearance model

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Photometric stereo with general, unknown lighting

Photometric stereo with general, unknown lighting

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conference on computer Vision and pattern recognition (CVPR)

作者： R. Basri D. Jacobs Department of Computer Science Weizmann Institute of Science Rehovot Israel NEC Research Institute Inc. Princeton NJ USA

ISBN: (纸本)0769512720

Work on photometric stereo has shown how to recover the shape and reflectance properties of an object using multiple images taken with a fixed viewpoint and variable lighting conditions. This work has primarily relied on the presence of a single point source of light in each image. The authors show how to perform photometric stereo, assuming that all lights in a scene are isotropic and distant from the object but otherwise unconstrained. Lighting in each image may be an unknown and arbitrary combination of diffuse, point and extended sources. Our work is based on recent results showing that for Lambertian objects, general lighting conditions can be represented using low order spherical harmonics. Using this representation, we can recover shape by performing a simple optimization in a low-dimensional space. We also analyze the shape ambiguities that arise in such a representation.

关键词： Photometry Shape Lighting control Layout Surface fitting computer science Reflectivity Laboratories Jacobian matrices National electric code

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