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IEEE Symposium on Intelligent Vehicle

作者： Daniel Biedermann Matthias Ochs Rudolf Mester Visual Sensorics & Information Processing Lab Goethe University Frankfurt am Main Germany ISY Linköping University Sweden

ISBN: (纸本)9781509018222

We present a framework that supports the development and evaluation of vision algorithms in the context of driver assistance applications and traffic surveillance. This framework allows the creation of highly realistic image sequences featuring traffic scenarios. The sequences are created with a realistic state of the art vehicle physics model; different kinds of environments are featured, thus providing a wide range of testing scenarios. Due to the physically-based rendering technique and variable camera models employed for the image rendering process, we can simulate different sensor setups and provide appropriate and fully accurate ground truth data.

关键词： Vehicles Rendering (computer graphics) Cameras Three-dimensional displays Lighting Roads Engines

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Keypoint trajectory estimation using propagation based tracking

Keypoint trajectory estimation using propagation based track...

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IEEE Symposium on Intelligent Vehicle

作者： Nolang Fanani Matthias Ochs Henry Bradler Rudolf Mester Visual Sensorics & Information Processing Lab Goethe University Frankfurt am Main Germany ISY Linköping University Sweden

ISBN: (纸本)9781509018222

One of the major steps in visual environment perception for automotive applications is to track keypoints and to subsequently estimate egomotion and environment structure from the trajectories of these keypoints. This paper presents a propagation based tracking method to obtain the 2D trajectories of keypoints from a sequence of images in a monocular camera setup. Instead of relying on the classical RANSAC to obtain accurate keypoint correspondences, we steer the search for keypoint matches by means of propagating the estimated 3D position of the keypoint into the next frame and verifying the photometric consistency. In this process, we continuously predict, estimate and refine the frame-to-frame relative pose which induces the epipolar relation. Experiments on the KITTI dataset as well as on the synthetic COnGRATS dataset show promising results on the estimated courses and accurate keypoint trajectories.

关键词： Trajectory Three-dimensional displays Estimation Tracking Cameras Vehicles Automotive engineering

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Learning relative photometric differences of pairs of cameras

Learning relative photometric differences of pairs of camera...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Christian Conrad Rudolf Mester Visual Sensorics & Information Processing Lab (VSI) Goethe University Frankfurt Germany Computer Vision Laboratory Linkoping University Sweden

We present an approach to learn relative photometric differences between pairs of cameras, which have partially overlapping fields of views. This is an important problem, especially in appearance based methods to correspondence estimation or object identification in multi-camera systems where grey values observed by different cameras are processed. We model intensity differences among pairs of cameras by means of a low order polynomial (Gray Value Transfer Function - GVTF ) which represents the characteristic curve of the mapping of grey values s i produced by camera C i to the corresponding grey values s j acquired with camera C j . While the estimation of the GVTF parameters is straight forward once a set of truly corresponding pairs of grey values is available, the non trivial task in the GVTF estimation process solved in this paper is the extraction of corresponding grey value pairs in the presence of geometric and photometric errors. We also present a temporal GVTF update scheme to adapt to gradual global illumination changes, e.g., due to the change of daylight.

关键词： Cameras Lighting Noise Transfer functions Histograms Tensile stress Estimation

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When Patches Match -- A Statistical View on Matching under Illumination Variation

When Patches Match -- A Statistical View on Matching under I...

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International Conference on Pattern Recognition

作者： Rudolf Mester Christian Conrad Visual Sensorics & Information Processing Lab (VSI) Goethe University Frankfurt Germany E.E. Dept (ISY) Linköping University Sweden

ISBN: (纸本)9781479952106

We discuss matching measures (scores and residuals) for comparing image patches under unknown affine photometric (=intensity) transformations. In contrast to existing methods, we derive a fully symmetric matching measure which reflects the fact that both copies of the signal are affected by measurement errors ('noise'), not only one. As it turns out, this evolves into an Eigen system problem, however a simple direct solution for all entities of interest can be given. We strongly advocate for constraining the estimated gain ratio and the estimated mean value offset to realistic ranges, thus preventing the matching scheme from locking into unrealistic correspondences.

关键词： Vectors Hidden Markov models Correlation Lighting Eigenvalues and eigenfunctions Standards Displacement measurement

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Local analysis of confidence measures for Optical Flow quality evaluation

Local analysis of confidence measures for Optical Flow quali...

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International Conference on Computer Vision Theory and Applications (VISAPP)

作者： Patricia Márquez-Valle Debora Gil Rudolf Mester Aura Hernàndez-Sabaté Computer Vision Center Universitat Autònoma de Barcelona Barcelona Spain Computer Vision Center Universitat Autònoma de Barcelona Edifici O - Campus UAB Bellaterra Spain Visual Sensorics and Information Processing Lab J. W. Goethe Universität Frankfurt Germany

ISBN: (纸本)9781479976867

Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance.

关键词： Measurement uncertainty Adaptive optics Optical variables measurement Optical imaging Current measurement Optical sensors Computational modeling

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2011年 6835 LNCS卷 V-VII页

作者： Mester, Rudolf Felsberg, Michael Johann-Wolfgang Goethe University Visual Sensorics and Information Processing Lab. 60054 Frankfurt/Main Germany Linköping University Department of Electrical Engineering 58183 Linköping Sweden

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Minimum variance image interpolation from noisy and aliased samples

Minimum variance image interpolation from noisy and aliased ...

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IEEE Southwest Symposium on Image Analysis and Interpretation

作者： A. Guevara R. Mester Visual Sensorics and Information Processing (VSI) Lab Goe University Frankfurt Germany

ISBN: (纸本)9781424478019

Interpolation of signals from a discrete set of noisy samples is addressed from a statistical standpoint. We present a reconstruction formula which is optimum in the MMSE sense, for both continuous and discrete-modeled signals, in a form which is substantially simpler than this may appear from earlier publications on the subject. We also derive the required Wiener-style interpolation kernel to be applied in order to obtain an optimal reconstruction. For image signals, we compare the results obtained using the proposed method with the ones obtained from typical spline interpolation routines.

关键词： Interpolation Signal sampling Image reconstruction Signal processing Image sampling CMOS image sensors Kernel Spline Least squares methods Sampling methods

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SIGNAL RECONSTRUCTION FROM NOISY, ALIASED, AND NONIDEAL SAMPLES: WHAT LINEAR MMSE APPROACHES CAN ACHIEVE

SIGNAL RECONSTRUCTION FROM NOISY, ALIASED, AND NONIDEAL SAMP...

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European Signal processing Conference

作者： Alvaro Guevara Rudolf Mester Visual Sensorics and Information Processing Lab (VSI) Computer Science Dept. Goethe University

This paper addresses the problem of interpolating a (non-bandlimited) signal from a discrete set of noisy measurements obtained from non-δ sampling kernels. We present a linear estimation approach, assuming the signal is given by a continuous model for which first and second order moments are known. The formula provides a generalization of the well-known discrete-discrete Wiener style estimator, but does not necessarily involve Fourier domain considerations. Finally, some experiments illustrate the flexibility of the method under strong noise and aliasing effects, and shows how the input autocorrelation, the sampling kernel and the noise process shape the form of the optimal interpolating kernels.

关键词： signals Flexibility methods discrete set Seeds NUCLEOPORIN, 214-KD Noise calcium ammonium nitrate Interpolation formula Mini Mental State Examination Moment of force aliasing effect Flexibility Kernel Generalization

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'Featuring' optical rails: View-based robot guidance using orientation features on the sphere

'Featuring' optical rails: View-based robot guidance using o...

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2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

作者： Dederscheck, David Friedrich, Holger Lenhart, Christine Zahn, Martin Mester, Rudolf Goethe University Frankfurt Visual Sensorics and Information Processing Lab. Robert-Mayer-Str. 10 60325 Frankfurt am Main Germany

ISBN: (纸本)9781424444427

In this paper, we propose the extension of a view-based method for autonomous track following formerly introduced as Optical Rails by [3, 6], to vector-valued feature images. Instead of gray or color values, the whole analysis works on local orientations, extracted from omnidirectional input images and represented as low-frequency vector-valued view descriptors using spherical harmonics. New signal processing schemes on the sphere are presented for such view descriptors, allowing for efficient approximation, comparison, and differential motion estimation also for incomplete spherical signals. Track following is performed using only visual information, and no auxiliary guidance systems or odometry information is used. We present first results of track following with a mobile robot in an indoor environment, which demonstrates the feasibility of this novel approach. ©2009 IEEE.

关键词： Spheres

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Statistical Certainty Models in Image processing

Statistical Certainty Models in Image Processing

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IEEE/SP Workshop on Statistical Signal processing (SSP)

作者： Rudolf Mester Visual Sensorics and Information Processing Lab Computer Science Department Johann Wolfgang Goethe-University of Frankfurt Frankfurt Germany

This paper revisits the fundamental question of how uncertain or unknown signal values should be appropriately dealt with in signal and image processing. It puts the concept of certainty and applicability values proposed by Westin and Knutsson in contrast to a statistical model where the state of knowledge on individual signal values is expressed by expectation values and variances, while the structure of signals is espressed by covariance functions, or covariance matrices, respectively. Using this simple approach, and exploiting the power of the Gauss-Markov-Theorem, a linear signal processing framework is obtained which is both powerful, generally applicable, and encompasses the classical certainty/applicability approach, providing answers to the open issues in that classical theory.

关键词： Image processing Interpolation Filters Signal processing Convolution Smoothing methods information processing Computer science Covariance matrix Gaussian processes

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