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Uncertainty analysis of camera parameters computed with a 3D pattern

13th international conference on Image Analysis and Processing, ICIAP 2005

作者： Ricolfe-Viala, Carlos Sánchez-Salmerón, Antonio-José Department of Systems Engineering and Automatic Control Polytechnic University of Valencia Valencia Spain

ISBN: (纸本)3540288694

Camera calibration is a necessary step in 3D modeling in order to extract metric information from images. Computed camera parameters are used in a lot of computer vision applications which involves geometric computation. these applications use camera parameters to estimate the 3D position of a feature in the image. Depending on the accuracy of the computed camera parameter, the precision of the position of the image feature in the 3D scene vary. Moreover if previously the accuracy of camera parameters is known, one technique or another can be choose in order to improve the position of the feature in the 3D scene. Calibration process consists of a closed form solution followed by a non linear refinement. this non linear refinement gives always the best solution for a given data. For sure this solution is false since input data is corrupted with noise. then it is more interesting to obtain an interval in which camera parameters are contained more than an accurate solution which is always false. the aim of this paper is to present a method to compute the interval in which the camera parameter is included. Computation of this interval is based on the residual error of the optimization technique. It is know that calibration process consists of minimize an index. With the residual error of the index minimization an interval can be computed in which camera parameter is. this interval can be used as a measurement of accuracy of the calibration process. © Springer-Verlag Berlin Heidelberg 2005.

关键词： three dimensional computer graphics

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From local pattern mining to relevant bi-cluster characterization

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6th international Symposium on Intelligent Data Analysis, IDA 2005

作者： Pensa, Ruggero G. Boulicaut, Jean-François INSA Lyon LIRIS CNRS UMR 5205 F-69621 Villeurbanne Cedex France

ISBN: (纸本)3540287957

Clustering or bi-clustering techniques have been proved quite useful in many application domains. A weakness of these techniques remains the poor support for grouping characterization. We consider eventually large Boolean data sets which record properties of objects and we assume that a bi-partition is available. We introduce a generic cluster characterization technique which is based on collections of bi-sets (i.e., sets of objects associated to sets of properties) which satisfy some userdefined constraints, and a measure of the accuracy of a given bi-set as a bi-cluster characterization pattern. the method is illustrated on both formal concepts (i.e., "maximal rectangles of true values") and the new type of δ-bi-sets (i.e., "rectangles of true values with a bounded number of exceptions per column"). the added-value is illustrated on benchmark data and two real data sets which are intrinsically noisy: a medical data about meningitis and Plasmodium falciparum gene expression data. © *** Berlin Heidelberg 2005.

关键词： pattern recognition

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pattern detection using fast normalized neural networks

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15th international conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005

作者： El-Bakry, Hazem M. University of Aizu Aizu Wakamatsu 965-8580 Japan

ISBN: (纸本)3540287523

Neural networks have shown good results for detecting of a certain pattern in a given image. In our previous papers [1-6], a fast algorithm for object/face detection was presented. Such algorithm was designed based on cross correlation in the frequency domain between the input image and the weights of neural networks. Our previous work also solved the problem of local subimage normalization in the frequency domain. In this paper, the effect of image normalization on the speed up ratio of pattern detection is presented. Simulation results show that local subimage normalization through weight normalization is faster than subimage normalization in the spatial domain. Moreover, the overall speed up ratio of the detection process is increased as the normalization of weights is done off line. © Springer-Verlag Berlin Heidelberg 2005.

关键词： pattern recognition

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Low-level cursive word representation based on geometric decomposition

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4th international conference on Machine Learning and Data Mining in pattern recognition, MLDM 2005

作者： Dong, Jian-Xiong Krzyzak, Adam Suen, Ching Y. Ponson, Dominique IMDS Software 75 rue Queen Montréal Que. H3C 2N6 Canada Center for Pattern-Recognition and Machine Intelligence Concordia University Montréal Que. H3G 1M8 Canada Department of Computer Science and Software Engineering Concordia University 1455 de Maisonneuve Blvd. W. Montréal Que. H3G 1M8 Canada

ISBN: (纸本)3540269231

An efficient low-level word image representation plays a crucial role in general cursive word recognition. this paper proposes a novel representation scheme, where a word image can be represented as two sequences of feature vectors in two independent channels, which are extracted from vertical peak points on the upper external contour and at vertical minima on the lower external contour, respectively. A data-driven method based on support vector machine is applied to prune and group those extreme points. Our experimental results look promising and have indicated the potential of this low-level representation for complete cursive handwriting recognition. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Image analysis

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Hierarchical watersheds within the combinatorial pyramid framework

Hierarchical watersheds within the combinatorial pyramid fra...

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12th international conference on Discrete Geometry for Computer Imagery, DGCI 2005

作者： Brun, Luc Mokhtari, Myriam Meyer, Fernand GreyC CNRS UMR 6072 Équipe Image - Ensicaen 6 Boulevard du Maréchal Juin 14050 CAEN Cedex France 35 rue Saint Honoré 77305 Fontainebleau Cedex France

Watershed is one of the most popular tool defined by mathematical morphology. the algorithms which implement the watershed transform generally produce an over segmentation which includes the right image's boundaries. Based on this last assumption, the segmentation problem turns out to be equivalent to a proper valuation of the saliency of each contour. Using such a measure, hierarchical watershed algorithms use the edge's saliency conjointly with statistical tests to decimate the initial partition. On the other hand, Irregular Pyramids encode a stack of successively reduced partitions. Combinatorial Pyramids consitute the latest model of this family. Within this framework, each partition is encoded by a combinatorial map which encodes all topological relationships between regions such as multiple boundaries and inclusion relationships. Moreover, the combinatorial pyramid framework provides a direct access to the embedding of the image's boundaries. We present in this paper a hierarchical watershed algorithm based on combinatorial pyramids. Our method overcomes the problems connected to the presence of noise both within the basins and along the watershed contours. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Watersheds

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Local characterization of a maximum set of digital (26,6)-surfaces

Local characterization of a maximum set of digital (26,6)-su...

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12th international conference on Discrete Geometry for Computer Imagery, DGCI 2005

作者： Ciria, Jose C. De Miguel, Angel Domínguez, Eladio Francés, Angel R. Quintero, Antonio Dpt. de Informática e Ingeniería de Sistemas Facultad de Ciencias Universidad de Zaragoza E-50009 - Zaragoza Spain Dpt. de Geometría y Topología Facultad de Matemáticas Universidad de Sevilla Apto. 1160 E-41080 - Sevilla Spain

this paper provides a local characterization for a set of digital surfaces SU defined in by mean of continuous analogues. For this, we firstly identify the set of admisible plates for any surface S ∈ SU (i.e., the intersection S ∩ C of S with a unit cube C of 3). then, the characterization is given in terms of a graph representing the intersection of plates. In addition, we establish a further condition that detects the digital surfaces in SU which are strongly separating objects. the family SU consists of all objects which are a digital surface in some homogeneous (26,6)-connected digital space in the sense of . Moreover, the subset of strongly separating surfaces of S U contains the family of simplicity 26-surfaces and other surfaces in literature as well. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Image processing

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Data distribution *** for domain decomposition applications in Grid environments

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6th international conference on Algorithms and Architectures for Parallel Processing, ICA3PP

作者： Otero, Beatriz Cela, José M. Badia, Rosa M. Labarta, Jesús Dpt. d'Arquitectura de Computadors Universitat Politècnica de Catalunya Campus Nord C/ Jordi Girona 1-3 Modul D6 109 08034 Barcelona Spain

ISBN: (纸本)3540292357

In this paper, we evaluate message-passing applications in Grid environments using domain decomposition technique. We compare two domain decomposition strategies: a balanced and unbalanced one. the balanced strategy is commonly strategy used in homogenous computing environment. this strategy presents some problems related with the larger communication latency in Grid environments. We propose an unbalanced domain decomposition strategy in order to overlap communication latency with useful computation. this idea consists in assigning less workload to processors responsible for sending updates outside the host. We compare the results obtained with the classical balanced strategy. We show that the unbalanced distribution pattern improves the execution times of domain decomposition applications in Grid environments. We considered two kinds of meshes, which define the most typical cases. We show that the expected execution time can be reduced up to 53%. We also analyze the influence of the communication patterns on execution times using the Dimemas simulator. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Distributed computer systems

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Measuring over-generalization in the minimal multiple generalizations of biosequences 1

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8th international conference on Discovery Science, DS 2005

作者： Ng, Yen Kaow Ono, Hirotaka Shinohara, Takeshi Kyushu Institute of Technology Graduate School of Computer Science and Systems Iizuka 820 Japan Kyushu University Department of Computer Science and Communication Engineering 6-10-1 Hakozaki Fukuoka 812-8581 Japan Kyushu Institute of Technology Department of Artificial Intelligence Iizuka 820 Japan

ISBN: (数字)9783540316985

ISBN: (纸本)3540292306

We consider the problem of finding a set of patterns that best characterizes a set of strings. To this end, Arimura et. al. [3] considered the use of minimal multiple generalizations (mmg) for such characterizations. Given any sample set, the mmgs are, roughly speaking, the most (syntactically) specific set of languages containing the sample within a given class of languages. Takae et. al. [17] found the mmgs of the class of pattern languages [1] which includes so-called sort symbols to be fairly accurate as predictors for signal peptides. We first reproduce their results using updated data. then, by using a measure for estimating the level of over-generalizations made by the mmgs, we show results that explain the high level of accuracies resulting from the use of sort symbols, and discuss how better results can be obtained. the measure that we suggests here can also be applied to other types of patterns, e.g. the PROSITE patterns [4]. © Springer-Verlag Berlin Heidelberg 2005.

关键词： pattern recognition

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Proceedings Sixth international conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS international Workshop on Self-Assembling Wireless Networks SNPD/SAWN 2005

Proceedings Sixth International Conference on Software Engin...

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6th international conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and 1st ACIS international Workshop on Self-Assembling Wireless Networks, SNPD/SAWN 2005

ISBN: (纸本)0769522947

the proceedings contain 71 papers. the topics discussed include: soft computing algorithms applied to the segmentation of nerve cell images;pattern recognition based on time-frequency distributions of radar micro-Doppler dynamics;a quantitative software quality evaluation model for the artifacts of component based development;a new approach to software requirements elicitation;using data mining technology to design an intelligent CIM system for IC manufacturing;data mining for imprecise temporal associations;analysis of breast cancer using data mining and statistical techniques;analyzing the conditions of coupling existence based on program slicing and some abstract information-flow;a study of model layers and reflection;a general scalable implementation of fast matrix multiplication algorithms on distributed memory computers;error prediction for multi-classification;an integer support vector machine;and layered neural networks computations.

关键词： Software engineering

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Predicting protein stability changes from sequences using support vector machines

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bioinformatics 2005年第Sup2期21卷 54-58页

作者： Capriotti, E Fariselli, P Calabrese, R Casadio, R Univ Bologna Dept Biol CIRB Lab Biocomp Bologna Italy

Motivation: the prediction of protein stability change upon mutations is key to understanding protein folding and misfolding. At present, methods are available to predict stability changes only when the atomic structure of the protein is available. Methods addressing the same task starting from the protein sequence are, however, necessary in order to complete genome annotation, especially in relation to single nucleotide polymorphisms (SNPs) and related diseases. Results: We develop a method based on support vector machines that, starting from the protein sequence, predicts the sign and the value of free energy stability change upon single point mutation. We show that the accuracy of our predictor is as high as 77% in the specific task of predicting the Delta Delta G sign related to the corresponding protein stability. When predicting the Delta Delta G values, a satisfactory correlation agreement with the experimental data is also found. As a final blind benchmark, the predictor is applied to proteins with a set of disease-related SNPs, for which thermodynamic data are also known. We found that our predictions corroborate the view that disease-related mutations correspond to a decrease in protein stability. Availability: http://***/cgi/predictors/I-Mutant2.0/***.

关键词： Algorithms Amino Acid Sequence Amino Acid Substitution Artificial Intelligence Computer Simulation Models, Chemical Molecular Sequence Data pattern recognition, Automated/methods Protein Denaturation Protein Denaturation Protein Folding Proteins/chemistry Sequence Alignment/methods Sequence Analysis, Protein/methods Structure-Activity Relationship

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