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检索条件"任意字段=3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007"

共 76 条记录，以下是51-60 订阅

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Analytic reconstruction of transparent and opaque surfaces from texture images

Analytic reconstruction of transparent and opaque surfaces f...

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3rd iberian conference on pattern recognition and image analysis

作者： Fanany, Mohamad Ivan Kumazawa, Itsuo Tokyo Inst Technol Tokyo 152 Japan

ISBN: (纸本)9783540728481

This paper addresses the problem of reconstructing non-overlapping transparent and opaque surfaces from multiple view images. The reconstruction is attained through progressive refinement of an initial 3D shape by minimizing the error between the images of the object and the initial 3D shape. The challenge is to simultaneously reconstruct both the transparent and opaque surfaces given only a limited number of images. Any refinement methods can theoretically be applied if analytic relation between pixel value in the training images and vertices position of the initial 3D shape is known. This paper investigates such analytic relations for reconstructing opaque and transparent surfaces. The analytic relation for opaque surface follows diffuse reflection model, whereas for transparent surface follows ray tracing model. However, both relations can be converged for reconstruction both surfaces into texture mapping model. To improve the reconstruction results several strategies including regularization, hierarchical learning, and simulated annealing are investigated.

关键词： image reconstruction

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A snake for retinal vessel segmentation

A snake for retinal vessel segmentation

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3rd iberian conference on pattern recognition and image analysis

作者： Espona, L. Carreira, M. J. Ortega, M. Penedo, M. G. Univ Santiago de Compostela Comp Vis Grp Dpto Elect & Computac Santiago De Compostela Spain Univ A Coruna Grp VARPA Dept Comp Coruna Spain

ISBN: (纸本)9783540728481

This paper presents an innovative methodology to detect the vessel tree in retinal angiographies. The automatic analysis of retinal vessel tree facilitates the computation of the arteriovenous index, which is essential for the diagnosis of a wide range of eye diseases. We have developed a system inspired in the classical snake but incorporating domain specific knowledge, such as blood vessels topological properties. It profites mainly from the automatic localization of the optic disc and from the extraction and enhancement of the vascular tree centerlines. Encouraging results in the detection of arteriovenous structures are efficiently achieved, as shown by the systems performance evaluation on the publicy available DRIVE database.

关键词： image segmentation

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Modeling aceto-white temporal patterns to segment colposcopic images

Modeling aceto-white temporal patterns to segment colposcopi...

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3rd iberian conference on pattern recognition and image analysis

作者： Acosta-Mesa, Hector-Gabriel Cruz-Ramirez, Nicandro Hernandez-Jimenez, Rodolfo Garcia-Lopez, Daniel-Alejandro Univ Veracruz Fac Phys & Artificial Intelligence Dept Artificial Intelligence Sebastian Camacho 5 Xalapa 91000 Veracruz Mexico Obstetrician & Gynaecologist Xalapa 91000 Veracruz Mexico

ISBN: (纸本)9783540728481

Colposcopy test is the second most used technique to diagnose cervical cancer disease. Some researchers have proposed to use temporal changes intrinsic to the colposcopic image sequences to automatically characterize cervical lesion. Under this approach, every single pixel on the image is represented as a Time Series of length equal to the sampling frequency times acquisition points. Although this approach seems to show promising results, the data analysis procedures have to deal with huge data set that rapidly increase with the number of cases (patients) considered in the analysis. In the present work, we perform principal component analysis (PCA) to reduce the dimensionality of the data in order to facilitate similarity measures for classification and clustering. The importance of this work is that we propose a model to parameterize the dynamics of the system using an efficient representation getting a 1.11% data compression ratio and similarity on clustering of 0.78. The feasibility of the proposed model is shown testing the similarity of the clusters generated using the k-means algorithm over the raw data and the compressed representation of real data.

关键词： pattern recognition

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Optimized associative memories for feature selection

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3rd iberian conference on pattern recognition and image analysis

作者： Aldape-Perez, Mario Yanez-Marquez, Cornelio Arguelles-Cruz, Amadeo Jose IPN Ctr Comp Res CIC Mexico City 07738 DF Mexico

ISBN: (纸本)9783540728467

Performance in most pattern classifiers is improved when redundant or irrelevant features are removed, however, this is mainly achieved by high demanding computational methods or successive classifiers construction. This paper shows how Associative Memories can be used to get a mask value which represents a subset of features that clearly identifies irrelevant or redundant information for classification purposes, therefore, classification accuracy is improved while significant computational costs in the learning phase are reduced. An optimal subset of features allows register size optimization, which contributes not only to significant power savings but to a smaller amount of synthesized logic, furthermore, improved hardware architectures are achieved due to functional units size reduction, as a result, it is possible to implement parallel and cascade schemes for pattern classifiers on the same ASIC.

关键词： feature selection pattern classifier masking techniques supervised learning

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Improving piecewise-linear registration through mesh optimization

Improving piecewise-linear registration through mesh optimiz...

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3rd iberian conference on pattern recognition and image analysis

作者： Arevalo, Vicente Gonzalez, Javier Univ Malaga Dept Syst Engn & Automat Campus Teatinos E-29071 Malaga Spain

ISBN: (纸本)9783540728481

Piecewise-linear methods accomplish the registration by dividing the images in corresponding triangular patches, which are individually mapped through affine transformations. For this process to be successful, every pair of corresponding patches must lie on projections of a 3D plane surface;otherwise, the registration may generate undesirable artifacts, such as broken lines, which diminish the registration quality. This paper presents a new technique for improving the registration consistency by automatically refining the topology of the corresponding triangular meshes used by this method. Our approach iteratively modifies the connectivity of the meshes by swapping edges. For detecting the edges to be swapped, we analyze the local registration consistency before and after applying the action, employing for that the mutual information (MI), a metric for registration consistency significantly more robust than other well-known metrics such as normalized cross correlation (NCC) or sum of square differences (SSD). The proposed method has been successfully tested with different sets of test images, both synthetic and real.

关键词： image registration

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Evaluation of spectral-based methods for median graph computation

Evaluation of spectral-based methods for median graph comput...

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3rd iberian conference on pattern recognition and image analysis

作者： Ferrer, Miquel Serratosa, Francesc Valveny, Ernest Univ Autonoma Barcelona Dept Ciencies Comp Comp Vis Ctr Bellaterra Spain Univ Rovira Virgili Dept Engn Informat Math Tarragona Spain

ISBN: (纸本)9783540728481

The median graph is a useful tool to cluster a set of graphs and obtain a prototype of them. The spectral graph theory is another approach to represent graphs and find "good" approximate solutions for the graph-matching problem. Recently, both approaches have been put together and a new representation has emerged, which is called Spectral-Median Graphs. In this paper, we summarize and compare two techniques to synthesize a Spectral-Median Graph: one is based on the correlation of the modal matrices and the other one is based on the averaging of the spectral modes. Results show that, although both approaches obtain good prototypes of the clusters, the first one is slightly more robust against the noise than the second one.

关键词： pattern matching

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Improving background subtraction based on a casuistry of colour-motion segmentation problem

Improving background subtraction based on a casuistry of col...

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3rd iberian conference on pattern recognition and image analysis

作者： Huerta, I. Rowe, D. Mozerov, M. Gonzalez, J. Comp Vis Ctr Dept Informat Edifici O Campus UAB Bellaterra 08193 Spain UPC Inst Robot & Informat Ind Barcelona 08028 Spain

ISBN: (纸本)9783540728481

The basis for the high-level interpretation of observed patterns of human motion still relies on motion segmentation. Popular approaches based on background subtraction use colour information to model each pixel during a training period. Nevertheless, a deep analysis on colour segmentation problems demonstrates that colour segmentation is not enough to detect all foreground objects in the image, for instance when there is a lack of colour necessary to build the background model. In this paper, our segmentation procedure is based not only on colour, but also on intensity information. Consequently, the intensity model enhances segmentation when the use of colour is not feasible. Experimental results demonstrate the feasibility of our approach.

关键词： image segmentation

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Bayesian hyperspectral image segmentation with discriminative class learning

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3rd iberian conference on pattern recognition and image analysis

作者： Borges, Janete S. Bioucas-Dias, Jose M. Marcal, Andre R. S. Univ Porto Fac Ciencias Rua Campo Alegre 823 P-4100 Oporto Portugal Inst Super Tecnic Inst Telecom Lisbon Portugal

ISBN: (纸本)9783540728467

This paper presents a new Bayesian approach to hyperspectral image segmentation that boosts the performance of the discriminative classifiers. This is achieved by combining class densities based on discriminative classifiers with a Multi-Level Logistic Markov-Gibs prior. This density favors neighbouring labels of the same class. The adopted discriminative classifier is the Fast Sparse Multinomial Regression. The discrete optimization problem one is led to is solved efficiently via graph cut tools. The effectiveness of the proposed method is evaluated, with simulated and real AVIRIS images, in two directions: 1) to improve the classification performance and 2) to decrease the size of the training sets.

关键词： image segmentation

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analysis of relevant maxima in distance *** application to fast coarse image segmentation

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3rd iberian conference on pattern recognition and image analysis

作者： Anton-Canalis, Luis Hernandez-Tejera, Mario Sanchez-Nielsen, Elena Univ Las Palmas Gran Canaria Inst Intelligent Syst & Numer Applicat Engn IUSIANI Campus Univ Tafira Las Palmas Gran Canaria Spain Univ Laguna Dept Estad Invest Operat & Comput Tenerife 38271 Spain

ISBN: (纸本)9783540728467

The Distance Transform is a powerful tool that has been used in many computer vision tasks. In this paper, the use of relevant maxima in distance transform's medial axis is proposed as a method for fast image data reduction. These disc-shaped maxima include morphological information from the object they belong to, and because maxima are located inside homogeneous regions, they also sum up chromatic information from the pixels they represent. Thus, maxima can be used instead of single pixels in algorithms which compute relations among pixels, effectively reducing computation times. As an example, a fast method for color image segmentation is proposed, which can also be used for textured zones detection. Comparisons with mean shift segmentation algorithm are shown.

关键词： image segmentation

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Region-based pose tracking

Region-based pose tracking

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3rd iberian conference on pattern recognition and image analysis

作者： Schmaltz, Christian Rosenhahn, Bodo Brox, Thomas Cremers, Daniel Weickert, Joachim Wietzke, Lennart Sommer, Gerald Univ Saarland Fac Math & Comp Sci Math Image Anal Grp Bldg E1 1 D-66041 Saarbrucken Germany Max Planck Inst Informat D-66123 Saarbrucken Germany Univ Bonn Dept Comp Sci D-53117 Bonn Germany Univ Kiel Inst Comp Sci D-24098 Kiel Germany

ISBN: (纸本)9783540728481

This paper introduces a technique for region-based pose tracking without the need to explicitly compute contours. We assume a surface model of a rigid object and at least one calibrated camera view. The goal is to find the pose parameters that optimally fit the model surface to the contour of the object seen in the image. In contrast to conventional contour-based techniques, which acquire the contour to be extracted explicitly from the image, our approach optimizes an energy directly defined on the pose parameters. We show experimental results for rather challenging scenes observed with a monocular and a stereo camera system.

关键词： Tracking (position)

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