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Carving Prior Manifolds Using Inequalities

Carving Prior Manifolds Using Inequalities

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Martin Eriksson Stefan Carlsson Numerical Analysis and Computer Science Royal Institute of Technology Stockholm Sweden

The use of prior information by learning from training data is used increasingly in image analysis and computer vision. The high dimensionality of the parameter spaces and the complexity of the probability distributions however often makes the exact learning of priors an impossible problem, requiring an excessive amount of training data that is seldom realizable in practise. In this paper we propose a weaker form of prior estimation which tries to learn the boundaries of impossible events from examples. This is equivalent to estimating the support of the prior distribution or the manifold of possible events. The idea is to model the set of possible events by algebraic inequalities. Learning proceeds by selecting those inequalities that show a consistent sign when applied to the training data set. Every such inequality "carves" out a region of impossible events in the parameter space. The manifold of possible events estimated in this way will in general represent the qualitative properties of the events. We give example of this in the problems of restoration of handwritten characters and automatically tracked body locations

关键词： Shape Manifolds Training Smoothing methods Humans Bayesian methods Training data

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A branch-and-bound technique for nano-structure image segmentation

A branch-and-bound technique for nano-structure image segmen...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Yoram Gat Intel research Santa Clara CA USA

Images of nano-structures are often noisy. On the other hand, in many settings there is quite a lot of model knowledge regarding the observed structures. This paper proposes a method for segmenting an image using a geometric model of the the observed structure. The resulting segmentation is guaranteed to be globally optimal, for an explicitly specified score function. This property provides a great deal of robustness to the algorithm. The algorithm presented explores a pre-defined space of segmentations using a branch-and-bound algorithm. It eliminates those parts of the space that are provably poor and explores in further detail the more promising parts of the space. An example of a segmentation that can be obtained in this way is a straight line segmentation of an image into 2 regions that minimizes the intensity variation within the regions. Results showing extraction of specific nano-structures are presented. A trivial variation on the algorithm can find a maximum a-posteriori probability estimate of the segmentation when there exists an a-priori distribution over the segmentations and the objective function is interpreted as the likelihood of the image given the segmentation.

关键词： Image segmentation Shape Pixel Image edge detection conferences Refining computer vision

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An Efficient Dynamic Multi-Angular Feature Points Matcher for Catadioptric Views

An Efficient Dynamic Multi-Angular Feature Points Matcher fo...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Sio-hoi Ieng Ryad Benosman Jean Devars Laboratory of Instruments and Systems of Ile de France University Pierre and Marie Curie Paris France

A new efficient matching algorithm dedicated to catadioptric sensors is proposed in this paper. The presented approach is designed to overcome the varying resolution of the mirror. The aim of this work is to provide a matcher that gives reliable results similar to the ones obtained by classical operators on planar projection images. The matching is based on a dynamical size windows extraction, computed from the viewing angular aperture of the neighborhood around the points of interest. An angular scaling of this angular aperture provides a certain number of different neighborhood resolution around the same considered point. A combinatory cost method is introduced in order to determine the best match between the different angular neighborhood patches of two interest points. Results are presented on sparse matched corner points, that can be used to estimate the epipolar geometry of the scene in order to provide a dense 3D map of the observed environment.

关键词： Sensors Apertures Mirrors Pixel conferences Robustness computer vision

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Noise Adaptive Channel Smoothing of Low-Dose Images

Noise Adaptive Channel Smoothing of Low-Dose Images

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Hanno Scharr Michael Felsberg Per-Erik Forssen Intel Research Santa Clara CA USA Computer Vision Laboratory Linköping University Linkoping Sweden

Many nano-scale sensing techniques and image processing applications are characterized by noisy, or corrupted, image data. Unlike typical camera-based computer vision imagery where noise can be modeled quite well as additive, zero-mean white or Gaussian noise, nano-scale images suffer from low intensities and thus mainly from Poisson-like noise. In addition, noise distributions can not be considered symmetric due to the limited gray value range of sensors and resulting truncation of over- and underflows. In this paper we adapt B-spline channel smoothing to meet the requirements imposed by this noise characteristics. Like PDE-based diffusion schemes it has a close connection to robust statistics but, unlike diffusion schemes, it can handle non-zero-mean noises. In order to account for the multiplicative nature of Poisson noise the variance of the smoothing kernels applied to each channel is properly adapted. We demonstrate the properties of this technique on noisy nano-scale images of silicon structures and compare to anisotropic diffusion schemes that were specially adapted to this data.

关键词： Smoothing methods Noise Kernel Robustness Spline Channel estimation computer vision

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Gestural Hand Motion Oscillation and Symmetries for Multimodal Discourse: Detection and Analysis

Gestural Hand Motion Oscillation and Symmetries for Multimod...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Yingen Xiong Francis Quek Department of Computer Science and Engineering Wright State University Dayton OH USA

We address the detection and analysis of gestural hand motion oscillation and symmetries in natural speech. First, we extract hand motion trajectory signals from video dataset. Second, we present our windowed correlation coefficient approach for gestural symmetry extraction. The signs and magnitudes of the correlation coefficients in the cardinal directions of the subject's torso characterize the symmetries. Third, we present a wavelet-based approach that extracts the time-frequency properties of hand motion oscillation. By analyzing these frequency properties durations of homogeneous gestural oscillations are detected. Finally, we apply our approach to a real video dataset captured in candid conversation. We relate the hand motion oscillatory gestures and symmetric gestures to the phases of speech and multimodal discourse analysis. We demonstrate the ability of our algorithm to extract gestural symmetries and oscillations and show how symmetric gestures and oscillatory gestures correspond to natural discourse structure.

关键词： Oscillators Speech Correlation Trajectory Noise Time frequency analysis Floors

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Background Line Detection with A Stochastic Model

Background Line Detection with A Stochastic Model

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Yefeng Zheng Huiping Li David Doermann Language and Media Processing Laboratory Institute for Advanced Computer Studies University of Maryland College Park MD USA

Background lines often exist in textual documents. It is important to detect and remove those lines so text can be easily segmented and recognized. A stochastic model is proposed in this paper which incorporates the high level contextual information to detect severely broken lines. We observed that 1) background lines are parallel, and 2) the vertical gaps between any two neighboring lines are roughly equal with small variance. The novelty of our algorithm is we use a HMM model to model the projection profile along the estimated skew angle, and estimate the optimal positions of all background lines simultaneously based on the Viterbi algorithm. Compared with our previous deterministic model based approach [15], the new method is much more robust and detects about 96.8% background lines correctly in our Arabic document database.

关键词： Hidden Markov models Pixel Distance measurement Decoding Stochastic processes Artificial intelligence Computational modeling

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Statistically Robust Approach to Lens Distortion Calibration with Model Selection

Statistically Robust Approach to Lens Distortion Calibration...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Moumen Taha El-Melegy Aly A. Farag Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Electrical Engineering Dept. Assiut University Assiut Egypt Computer Vision and Image Processing Lab. University of Louisville Louisville KY

This paper addresses the problem of calibrating camera lens distortion, which can be significant in medium to wide angle lenses. While almost all existing nonmetric distortion calibration methods need user involvement in one form or another,we present an approach to distortion calibration based on the robust the-least-median-of-squares (LMedS) estimator. Our approach is thus able to proceed in a ful ly-automatic manner while being less sensitive to erroneous input data such as image curves that are mistakenly considered as projections of 3D linear segments. Our approach uniquely uses fast, closed-form solutions to the distortion coefficients, which serve as an initial point for a non-linear optimization algorithm to straighten imaged lines. Moreover we propose a method for distortion model selection based on geometrical *** experiments to evaluate the performance of this approach on synthetic and real data are reported.

关键词： Nonlinear distortion Calibration Robustness Lenses Cameras Image edge detection Distortion measurement

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Handwritten Amharic Bank Check recognition Using Hidden Markov Random Field

Handwritten Amharic Bank Check Recognition Using Hidden Mark...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Worku Alemu Siegfried Fuchs Image Processing and Recognition Group Artificial Intelligence Institute Dresden Germany

Amharic, a working language in Ethiopia, has its own writing system which is totally different from that of the Latin alphabet based languages. Amharic handwriting recognition is challenging due to the huge number of symbols, significant interclass similarity and also intra-class variability. In this paper the application of Hidden Markov Random Field (HMRF) for handwriting recognition of the legal amount field of Amharic bank check is presented. The three main contributions of this paper are the following. First, a new feature extraction technique is used which tries to extract natural features as perceived by human beings. The features extracted by this technique show a significant performance improvement. Second, a classification technique by estimating likelihood using a method known as pseudo-marginal probability is developed. The third contribution is the application of contextual information based on the syntactical structure of Amharic checks. Such context information is important in recognition process because even humans fail to recognize symbols correctly without any context. A noticeable difference is observed between results obtained with and without the application of contextual information. On the whole, despite the huge interclass similarity and also intra-class variability of handwritten Amharic characters, attractive results are found.

关键词： Pixel Feature extraction Hidden Markov models Computational modeling Handwriting recognition pattern recognition Law

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Salient Features and Hypothesis Testing: evaluating a novel approach for segmentation and address block location

Salient Features and Hypothesis Testing: evaluating a novel ...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： David Menoti Dibio Leandro Borges Alceu de Souza Britto Jr Postgraduate Program in Applied Informatics (PPGIA) Pontifical Catholic University of Parana (PUCPR) Curitiba PR Brazil Pontifical Catholic University of Parana (PUCPR)

This paper presents a modification with further experiments of a segmentation algorithm based on feature selection in wavelet space of ours [9]. The aim is to automatically separate in postal envelopes the regions related to background, stamps, rubber stamps, and the address blocks. First, a typical image of a postal envelope is decomposed using Mallat algorithm and Haar basis. High frequency channel outputs are analyzed to locate salient points in order to separate the background. A statistical hypothesis test is taken to decide upon more consistent regions in order to clean out some noise left. The selected points are projected back to the original gray level image, where the evidence from the wavelet space is used to start a growing process to include the pixels more likely to belong to the regions of stamps, rubber stamps, and written area. We have modified the growing process controlled by the salient points and the results were greatly improved reaching success rate of over 97%. Experiments are run using original postal envelopes from the Brazilian Post Office Agency, and here we report results on 440 images with many different layouts and backgrounds.

关键词： Image segmentation Pixel Rubber Layout Wavelet transforms computer vision pattern recognition

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General Data Association with Possibly Unresolved Measurements Using Linear Programming

General Data Association with Possibly Unresolved Measuremen...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Huimin Chen Krishna Pattipati Thiagalingam Kirubarajan Yaakov Bar-Shalom Department of Electrical & Computer Engineering University of Connecticut Storrs CT USA Department of Electrical & Computer Engineering McMaster University Hamilton ONT Canada Department of Electrical Engineering University of New Orleans New Orleans LA USA

In this paper we formulate data association with possibly unresolved measurements as an augmented assignment problem. Unlike conventional measurement-to-track association via assignment, this augmented assignment problem has much greater complexity when each target originated measurement can be of single or multiple origins. The main point is that standard one-to-one assignment algorithms do not work in the case of unresolved measurements because the constraints in the augmented assignment problem are very different. A suboptimal approach is considered for solving the resulting optimization problem via linear programming (LP) by relaxing the integer constraints. A tracker based on probabilistic data association filter (PDAF) using the LP solutions is also discussed. Simulation results show that the percentage of track loss is significantly reduced by solving the augmented assignment rather than the conventional assignment.

关键词： Target tracking Radar tracking Time measurement Linear programming conferences Indexes Probabilistic logic

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