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共 8962 条记录，以下是4461-4470 订阅

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Integration of multiple contextual information for image segmentation using a Bayesian Network

Integration of multiple contextual information for image seg...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Lei Zhang Qiang Ji Rensselaer Polytechnic Institute Troy NY USA

We propose a Bayesian network (BN) model to integrate multiple contextual information and the image measurements for image segmentation. The BN model systematically encodes the contextual relationships between regions, edges and vertices, as well as their image measurements with uncertainties. It allows a principled probabilistic inference to be performed so that image segmentation can be achieved through a most probable explanation (MPE) inference in the BN model. We have achieved encouraging results on the horse images from the Weizmann dataset. We have also demonstrated the possible ways to extend the BN model so as to incorporate other contextual information such as the global object shape and human intervention for improving image segmentation. Human intervention is encoded as new evidence in the BN model. Its impact is propagated through belief propagation to update the states of the whole model. From the updated BN model, new image segmentation is produced.

关键词： Image segmentation Bayesian methods Shape Context modeling Humans computer vision Graphical models Belief propagation Active contours Layout

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Model-based mapping of a nonrigid image registration algorithm to heterogeneous architectures

Model-based mapping of a nonrigid image registration algorit...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Yashwanth Hemaraj Mainak Sen William Plishker Raj Shekhar Shuvra Bhattacharyya Department of Electrical and Computer Engineering University of Maryland College Park College Park MD USA

This work targets the design of customized accelerators for image registration algorithms, which are required for many important computer vision applications. By capturing key, domain-specific characteristics of application structure, signal-processing-oriented models of computation provide a valuable foundation for structured development of efficient image registration accelerators. Building upon the meta-modeling framework of homogeneous parameterized dataflow, we develop in this paper an approach for automatically generating streamlined implementations of image registration algorithms according to performance metrics such as image size, area and overall processing speed. Results from hardware synthesis demonstrate the efficiency of our methods. Our approach provides designers an effective way to explore different architectures, and systematically provide acceleration for high-performance nonrigid image registration based on a variety of requirements. Our dataflow-based framework can be adapted to explore different architectures for other kinds of image processing algorithms as well.

关键词： Image registration Application software computer architecture Algorithm design and analysis computer vision Computational modeling Buildings Metamodeling Streaming media Measurement

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Model-based perceptual grouping and shape abstraction

Model-based perceptual grouping and shape abstraction

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Pablo Sala Sven J. Dickinson University of Toronto Canada

Contour features are re-emerging in the categorization community as it moves from appearance back to shape. However, the classical assumption of one-to-one correspondence between an extracted image contour and a model contour constrains category models to be highly brittle, offering little abstraction between image and model. Moreover, todaypsilas contour-based models are category-specific, offering no mechanism for contour grouping and abstraction in the absence of an object prior. We present a novel framework for recovering a set of abstract parts from a multi-scale contour image. Given a user-specified part vocabulary and an image to be analyzed, the system covers the image with abstract part models drawn from the vocabulary. More importantly, correspondence between image contours and part contours is many-to-one, yielding a powerful shape abstraction mechanism. We illustrate the strengths and weaknesses of this work in progress on a set of anecdotal scenes.

关键词： Shape Vocabulary Layout Object detection Power system modeling Indexing Image analysis computer vision Face detection Feature extraction

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Non-rigid registration of 3D surfaces by deformable 2D triangular meshes

Non-rigid registration of 3D surfaces by deformable 2D trian...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Arman Savran Bulent Sankur Electrical and Electronics Engineering Department Bogazici University Istanbul Turkey

Non-rigid surface registration, particularly registration of human faces, finds a wide variety of applications in computer vision and graphics. We present a new automatic surface registration method which utilizes both attraction forces originating from geometrical and textural similarities, and stresses due to non-linear elasticity of the surfaces. Reference and target surfaces are first mapped onto their feature image planes, then these images are registered by subjecting them to local deformations, and finally 3D correspondences are established. Surfaces are assumed to be elastic sheets and are represented by triangular meshes. The internal elastic forces act as a regularizer in this ill-posed problem. Furthermore, the non-linear elasticity model allows us to handle large deformations, which can be essential, for instance, for facial expressions. The method has been tested successfully on 3D scanned human faces, with and without expressions. The algorithm runs quite efficiently using a multiresolution approach.

关键词： Humans Surface texture Elasticity Face detection Application software computer vision computer graphics Stress Deformable models Testing

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Codomain scale space and regularization for high angular resolution diffusion imaging

Codomain scale space and regularization for high angular res...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Luc Florack Department of Mathematics and Computer Science & Department of Biomedical Engineering Eindhovan University of Technology Eindhoven Netherlands

Regularization is an important aspect in high angular resolution diffusion imaging (HARDI), since, unlike with classical diffusion tensor imaging (DTI), there is no a priori regularity of raw data in the co-domain, i.e. considered as a multispectral signal for fixed spatial position. HARDI preprocessing is therefore a crucial step prior to any subsequent analysis, and some insight in regularization paradigms and their interrelations is compulsory. In this paper we posit a codomain scale space regularization paradigm that has hitherto not been applied in the context of HARDI. Unlike previous (first and second order) schemes it is based on infinite order regularization, yet can be fully operationalized. We furthermore establish a closed-form relation with first order Tikhonov regularization via the Laplace transform.

关键词： Image resolution High-resolution imaging Diffusion tensor imaging Space technology Biomedical imaging Laplace equations Tensile stress Mathematics computer science Biomedical engineering

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Pipeline landmark detection for autonomous robot navigation using time-of-flight imagery

Pipeline landmark detection for autonomous robot navigation ...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Jens T. Thielemann Goril M. Breivik Asbjorn Berge SINTEF ICT Oslo Norway

3D imaging systems provide valuable information for autonomous robot navigation based on landmark detection in pipelines. This paper presents a method for using a time-of-flight (TOF) camera for detection and tracking of pipeline features such as junctions, bends and obstacles. Feature extraction is done by fitting a cylinder to images of the pipeline. Data in captured images appear to take a conic rather than cylindrical shape, and we adjust the geometric primitive accordingly. Pixels deviating from the estimated cylinder/cone fit are grouped into blobs. Blobs fulfilling constraints on shape and stability over time are then tracked. The usefulness of TOF imagery as a source for landmark detection and tracking in pipelines is evaluated by comparison to auxiliary measurements. Experiments using a model pipeline and a prototype robot show encouraging results.

关键词： Pipelines Navigation Cameras Robot vision systems Robot sensing systems Inspection Simultaneous localization and mapping Shape Laser theory Ultrasonic imaging

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Gender classification from hand shape

Gender classification from hand shape

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Gholamreza Amayeh George Bebis Mircea Nicolescu Computer Vision Laboratory University of Nevada Reno NV USA

Many social interactions and services today depend on gender. In this paper, we investigate the problem of gender classification from hand shape. Our work has been motivated by studies in anthropometry and psychology suggesting that it is possible to distinguish between male and female hands by considering certain geometric features. Our system segments the hand silhouette into six different parts corresponding to the palm and fingers. To represent the geometry of each part, we use region and boundary features based on Zernike moments and Fourier descriptors. For classification, we compute the distance of a given part from two different eigenspaces, one corresponding to the male class and the other corresponding to female class. We have experimented using each part of the hand separately as well as fusing information from different parts of the hand. Using a small database containing 20 males and 20 females, we report classification results close to 98% using score-level fusion and LDA.

关键词： Shape Fingers Humans Face detection computer vision Psychology Data mining Robustness Laboratories Anthropometry

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Curvature preserving fingerprint ridge orientation smoothing using Legendre polynomials

Curvature preserving fingerprint ridge orientation smoothing...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Surinder Ram Horst Bischof Josef Birchbauer Institute for Computer Graphics and Vision Graz University of Technology Austria Siemens IT Solutions and Services Biometrics Center Siemens AG Austria

Smoothing fingerprint ridge orientation involves a principal discrepancy. Too little smoothing can result in noisy orientation fields (OF), too much smoothing will harm high curvature areas, especially singular points (SP). In this paper we present a fingerprint ridge orientation model based on Legendre polynomials. The motivation for the proposed method can be found by analysing the almost exclusively used method in literature for orientation smoothing, proposed by Witkin and Kass (1987) more than two decades ago. The main contribution of this paper argues that the vectorial data (sine and cosine data) should be smoothed in a coupled way and the approximation error should not be evaluated employing vectorial data. For evaluating the proposed method we use a Poincare-Index based SP detection algorithm. The experiments show, that in comparison to competing methods the proposed method has improved orientation smoothing capabilities, especially in high curvature areas.

关键词： Fingerprint recognition Smoothing methods Polynomials Biometrics Image quality computer graphics Approximation error Authentication Feature extraction Image matching

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Implementation of auto-rectification and depth estimation of stereo video in a real-time smart camera system

Implementation of auto-rectification and depth estimation of...

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Xinting Gao Richard Kleihorst Ben Schueler NXP Semiconductors Corporate I&T/Research Eindhoven The Netherlands

In this paper, we present a real-time, low power, and wireless embedded stereo vision system. The system consists of WiCa board (wireless camera board) and the methods developed using a smart camera processor, IC3D. IC3D is an SIMD video-analysis processor that has 320 processor elements. The proposed auto-rectification method is suitable for a parallel stereo system like WiCa. It is based on the matching of a planar background. After rectification, the two images of the background are coincident with each other, i.e., both the vertical and horizontal disparity of the background plane is removed. Then a dense matching method is implemented to achieve the depth map of the foreground object. Left-to-right checking and reliability checking is applied to reduce the error of the estimated depth. The system runs at 30 fps and handles disparity up to 37 pixels in CIF (320times240 pixels) mode.

关键词： Real time systems Smart cameras Stereo vision Costs Wireless sensor networks Image sensors Intelligent sensors Layout computer vision Video surveillance

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Playing games as a way to improve automatic image annotation

Playing games as a way to improve automatic image annotation

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ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Rui Jesus Duarte Goncalves Arnaldo J. Abrantes Nuno Correia Multimedia and Machine Learning Group Instituto Superior de Engenharia de Lisboa Monte da Caparica Portugal Interactive Multimedia Group CITI and DI FCT New University of Lisbon Portugal

Image annotation is hard to do in an automatic way. In this paper, we propose a framework for image annotation that combines the benefits of three paradigms: automatic annotation, human intervention and entertainment activities. We also describe our proposal inside this framework, the ASAA (application for semi-automatic annotation) interface, a new computer game for image tagging. The application has a 3D game interface, and is supported by a game engine that uses a system for automatic image classification and gestural input to play the game. We present results of the performance of semantic models obtained with a training set enlarged by images annotated during the game activity as well as usability tests of the application.

关键词： Humans Application software Image retrieval Proposals Tagging Image classification Usability Machine learning computer interfaces Engines

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