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conference on computer Vision and pattern recognition (CVPR)

作者： Y. Keller A. Averbuch Department of Computer Science Technion-Israel Institute of Technology Haifa Israel Department of Computer Science School of Mathematical Sciences Tel-Aviv University Tel-Aviv Israel

This paper presents an implicit similarity-based approach to registration of significantly dissimilar images, acquired by sensors at different modalities. The proposed algorithm introduces a robust matching criterion by aligning the locations of gradient maxima. The alignment is formulated as a parametric variational optimization problem, which is solved iteratively by considering the intensities of a single image. The location of the maxima of the second image's gradient are used as initialization. We are able to robustly estimate affine and projective global motions using 'coarse to fine' processing. even when the images are characterized by complex space varying intensity transformations. Finally, we present the registration of real images, which were taken by multi-sensor and multi-modality using affine and projective motion models.

关键词： image registration image sensors Robustness Magnetic resonance imaging Gradient methods computer science Sensor phenomena and characterization Remote sensing Biomedical imaging Computed tomography

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Range image segmentation by surface extraction using an improved robust estimator

Range image segmentation by surface extraction using an impr...

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conference on computer Vision and pattern recognition (CVPR)

作者： P.F.U. Gotardo O.R.P. Bellon L. Silva Departamento de Informatica Universidade Federal do Parana Brazil Centro Federal de Educacao Tecnologica do Parana CPGEI Brazil

The paper presents a novel range image segmentation algorithm based on planar surface extraction. The algorithm was applied to common range image databases and was favorably compared against seven other segmentation algorithms using a popular evaluation framework. The experimental results show that, as compared to the other methods, our algorithm presents a good performance in preserving small regions and edge locations when processing.noisy images. Our main contribution is an improved robust estimator, derived from the RANSAC and MSAC estimators, whose optimization process is accelerated by a genetic algorithm with a new set of parameters and operations designed to avoid premature convergence.

关键词： image segmentation Robustness Surface fitting computer vision Object recognition Layout Solid modeling Parameter estimation Genetic algorithms Convergence

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Polydioptric camera design and 3D motion estimation

Polydioptric camera design and 3D motion estimation

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conference on computer Vision and pattern recognition (CVPR)

作者： J. Neumann C. Fermuller Y. Aloimonos Computer Vision Laboratory University of Maryland College Park MD USA

Most cameras used in computer vision applications are still based on the pinhole principle inspired by our own eyes. It has been found though that this is not necessarily the optimal image formation principle for processing.visual information using a machine. We describe how to find the optimal camera for 3D motion estimation by analyzing the structure of the space formed by the light rays passing through a volume of space. Every camera corresponds to a sampling pattern in light ray space, thus the question of camera design can be rephrased as finding the optimal sampling pattern with regard to a given task. This framework suggests that large field-of-view multi-perspective (polydioptric) cameras are the optimal image sensors for 3D motion estimation. We conclude by proposing design principles for polydioptric cameras and describe an algorithm for such a camera that estimates its 3D motion in a scene independent and robust manner.

关键词： Cameras Motion estimation image sampling computer vision Application software Eyes image motion analysis image sensors Algorithm design and analysis Layout

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Progress in camera-based document image analysis 7

Progress in camera-based document image analysis

引用

7th International conference on Document Analysis and recognition, ICDAR 2003

作者： Doermann, David Liang, Jian Li, Huiping Language and Media Processing Laboratory Institute for Advanced Computer Studies University of Maryland College Park United States

ISBN: (纸本)0769519601

The increasing availability of high performance, low priced, portable digital imaging devices has created a tremendous opportunity for supplementing traditional scanning for document image acquisition. Digital cameras attached to cellular phones, PDAs, or as standalone still or video devices are highly mobile and easy to use;they can capture images of any kind of document including very thick books, historical pages too fragile to touch, and text in scenes;and they are much more versatile than desktop scanners. Should robust solutions to the analysis of documents captured with such devices become available, there is clearly a demand from many domains. Traditional scanner-based document analysis techniques provide us with a good reference and starting point, but they cannot be used directly on camera-captured images. Camera captured images can suffer from low resolution, blur, and perspective distortion, as well as complex layout and interaction of the content and background. In this paper we present a survey of application domains, technical challenges and solutions for recognizing documents captured by digital cameras. We begin by describing typical imaging devices and the imaging process. We discuss document analysis from a single camera-captured image as well as multiple frames and highlight some sample applications under development and feasible ideas for future development. © 2003 ieee.

关键词： Scanning

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On region merging: the statistical soundness of fast sorting, with applications

On region merging: the statistical soundness of fast sorting...

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conference on computer Vision and pattern recognition (CVPR)

作者： F. Nielsen R. Nock Sony CS Laboratories FRL Shinagawa Tokyo Japan DSI-Universite Antilles-Guyane Schoelcher France

This work explores a statistical basis for a process often described in computer vision: image segmentation by region merging following a particular order in the choice of regions. We exhibit a particular blend of algorithmics and statistics whose error is, as we formally show, close to the best possible. This approach can be approximated in a very fast segmentation algorithm for processing.images described using most common numerical feature spaces. Simple modifications of the algorithm allow us to cope with occlusions and/or hard noise levels. Experiments on grey-level and color images, obtained with a short C-code, display the quality of the segmentations obtained.

关键词： Merging Sorting image segmentation Application software computer vision Error analysis computer errors Noise level Color Displays

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Simultaneous structure and texture image inpainting

Simultaneous structure and texture image inpainting

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conference on computer Vision and pattern recognition (CVPR)

作者： M. Bertalmio L. Vese G. Sapiro S. Osher UCLA University Pompeu Fabra University of Minnesota USA

An algorithm for the simultaneous filling-in of texture and structure in regions of missing image information is presented. The basic idea is to first decompose the image into the sum of two functions with different basic characteristics, and then reconstruct each one of these functions separately with structure and texture filling-in algorithms. The first function used in the decomposition is of bounded variation, representing the underlying image structure, while the second function captures the texture and possible noise. The region of missing information in the bounded variation image is reconstructed using image inpainting algorithms, while the same region in the texture image is filled-in with texture synthesis techniques. The original image is then reconstructed adding back these two sub-images. The novel contribution of the paper is then in the combination of these three previously developed components: image decomposition with inpainting and texture synthesis, which permits the simultaneous use of filling-in algorithms that are suited for different image characteristics. Examples on real images show the advantages of this proposed approach.

关键词： image reconstruction image decomposition image coding Switches image processing image communication image restoration Filling image texture analysis Reconstruction algorithms

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Optical flow estimation in omnidirectional images using wavelet approach

Optical flow estimation in omnidirectional images using wave...

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ieee computer society conference on computer Vision and pattern recognition Workshops (CVPRW)

作者： Cedric Demonceaux Djemaa Kachi-Akkouche UMR 6140 L.A.M.F.A. Amiens France EA 3299 CREA Amiens France

The motion estimation computation in the image sequences is a significant problem in image processing. Many researches were carried out on this subject in the image sequences with a traditional camera. These techniques were applied in omnidirectional image sequences. But the majority of these methods are not adapted to this kind of sequences. Indeed they suppose the flow is locally constant but the omnidirectional sensor generates distortions which contradict this assumption. In this paper, we propose a fast method to compute the optical flow in omnidirectional image sequences. This method is based on a Brightness Change Constraint Equation decomposition on a wavelet basis. To take account of the distortions created by the sensor, we replace the assumption of flow locally constant used in traditional images by a hypothesis more appropriate.

关键词： computer vision image motion analysis Optical imaging Optical distortion Optical sensors Estimation Equations

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Example-based style synthesis

Example-based style synthesis

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conference on computer Vision and pattern recognition (CVPR)

作者： I. Drori D. Cohen-Or H. Yeshurun School of Computer Science Tel-Aviv University Tel-Aviv Israel

We introduce an example-based synthesis technique that extrapolates novel styles for a given input image. The technique is based on separating the style and content of image fragments. Given an image with a new style and content, it is first adaptively partitioned into fragments. Stitching together novel fragments produces a coherent image in a new style for a given content. The aggregate of synthesized fragments approximates a globally non-linear model with a set of locally linear models. We show the result of our method for various artistic, sketch, and texture filters and painterly styles applied to different image content classes.

关键词： computer vision computer science Aggregates Filters Painting Rendering (computer graphics) Table lookup Pixel computer society pattern recognition

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Shape-based recognition of wiry objects

Shape-based recognition of wiry objects

引用

conference on computer Vision and pattern recognition (CVPR)

作者： O. Carmichael M. Hebert The Robotics Institute Carnegie Mellon University Pittsburgh PA USA

We present an approach to the recognition of complex-shaped objects in cluttered environments based on edge cues. We first use example images of the desired object in typical backgrounds to train a classifier cascade which determines whether edge pixels in an image belong to an instance of the object or the clutter. Presented with a novel image, we use the cascade to discard clutter edge pixels. The features used for this classification are localized, sparse edge density operations. Experiments validate the effectiveness of the technique for recognition of complex objects in cluttered indoor scenes under arbitrary out-of-image-plane rotation.

关键词： image edge detection Pixel Shape Face detection Filtering Layout Lamps Object detection image recognition pattern recognition

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Evaluation of local models of dynamic backgrounds

Evaluation of local models of dynamic backgrounds

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conference on computer Vision and pattern recognition (CVPR)

作者： R. Pless J. Larson S. Siebers B. Westover Department of Computer Science and Engineering Washington University of Saint Louis USA

Background subtraction is the first step of many video surveillance applications. What is considered background varies by application, and may include regular, systematic, or complex motions. The paper explores the use of several different local spatio-temporal models of a background, defined at each pixel in the image. We present experiments with real image data and conclude that appropriate local representations are sufficient to make background models of complicated real world motions. Empirical studies illustrate, for example, that an optical flow-based model is able to detect emergency vehicles whose motion is different from those typically observed in traffic scenes. We conclude that "different models are appropriate for different scenes", but give criteria by which one can choose which model will be best.

关键词： Layout Pixel Video surveillance Application software Vehicle detection image processing Atomic measurements Video sequences Filters Vehicle dynamics

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