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Robust recognition of 1-D barcodes using camera phones

Robust recognition of 1-D barcodes using camera phones

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作者： Wachenfeld, Steffen Terlunen, Sebastian Jiang, Xiaoyi Department of Computer Science Computer Vision and Pattern Recognition Group University of Munster Germany

ISBN: (纸本)9781424421756

In this paper we present an algorithm for the recognition of 1D barcodes using camera phones, which is highly robust regarding the the typical image distortions. We have created a database of barcode images, which covers typical distortions, such as inhomogeneous illumination, reflections, or blurriness due to camera movement. We present results from experiments with over 1,000 images from this database using a Matlab implementation of our algorithm, as well as experiments on the go, where a Symbian C++ implementation running on a camera phone is used to recognize barcodes in daily life situations. The proposed algorithm shows a close to 100% accuracy in real life situations and yields a very good resolution dependent performance on our database, ranging from 90.5% (640 × 480) up to 99.2% (2592 × 1944). The database is freely available for other researchers. © 2008 IEEE.

关键词： Database systems

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Hidden Markov model-unscented Kalman filter contour tracking: A multi-cue and multi-resolution approach

Hidden Markov model-unscented Kalman filter contour tracking...

引用

Iranian Conference on Machine vision and Image Processing

作者： Moayedi, Fatemeh Kazemi, Alireza Azimifar, Zohreh Computer Vision and Pattern Recognition Group School of Electrical and Computer Engineering Shiraz University shiraz Iran

ISBN: (纸本)9781424497065

This paper present a novel attempt to introduce an HMM-based multi-resolution and multi-cue segmentation in combination with the unscented Kalman filter tracking method. It combines multiple features distribution and multiple resolutions to facilitate 2D video tracking. The advantages of this method lie in its speed and its robustness. Speed is dramatically improved by taking into account multiple resolutions which reduce number of measurement points (number of HMM states) while keeping its quality. Robustness is achieved by using multiple cues. We propose an algorithm to find an optimal operating point for a tracker in terms of the image scale. Furthermore, we propose a faster multi-scale (spatial) tracker based on a minimum acceptable performance limit. The proposed method is demonstrated on human head tracking with a non-stationary camera. Visual tests indicate that the optimized algorithms produce qualitatively better results. Results show that we are able to maintain real-time processing on quite generous video resolutions. Therefore it will be shown that our approach is faster and more efficient than conventional UKF and UKF with multi-cue. © 2010 IEEE.

关键词： Hidden Markov models

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Kernel-based recognition of human actions using spatiotemporal salient points

Kernel-based recognition of human actions using spatiotempor...

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2006 Conference on computer vision and pattern recognition Workshops

作者： Oikonomopoulos, A. Patras, I. Pantic, M. Computing Department Imperial College London Computer Vision and Pattern Recognition Group University of York

ISBN: (纸本)0769526462

This paper addresses the problem of human action recognition by introducing a sparse representation of image sequences as a collection of spatiotemporal events that are localized at points that are salient both in space and time. We detect the spatiotemporal salient points by measuring the variations in the information content of pixel neighborhoods not only in space but also in time. We derive a suitable distance measure between the representations, which is based on the Chamfer distance, and we optimize this measure with respect to a number of temporal and scaling parameters. In this way we achieve invariance against scaling, while at the same time, we eliminate the temporal differences between the representations. We use Relevance Vector Machines (RVM) in order to address the classification problem. We propose new kernels for use by the RVM, which are specifically tailored to the proposed spatiotemporal salient point representation. The basis of these kernels is the optimized Chamfer distance of the previous step. We present results on real image sequences from a small database depicting people performing 19 aerobic exercises. © 2006 IEEE.

关键词： pattern recognition

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Nonlinear shape statistics via kernel spaces 23rd

引用

23rd German Association for pattern recognition Symposium, DAGM 2001

作者： Cremers, Daniel Kohlberger, Timo Schnörr, Christoph Computer Vision Graphics and Pattern Recognition Group Department of Mathematics and Computer Science University of Mannheim Mannheim68131 Germany

ISBN: (纸本)3540425969

We present a novel approach for representing shape knowledge in terms of example views of 3D objects. Typically, such data sets exhibit a highly nonlinear structure with distinct clusters in the shape vector space, preventing the usual encoding by linear principal component analysis (PCA). For this reason, we propose a nonlinear Mercer-kernel PCA scheme which takes into account both the projection distanceand the within-subspace distance in a high-dimensional feature space. The comparison of our approach with supervised mixture models indicates that the statistics of example views of distinct 3D objects canfairly well be learned and represented in a completely unsupervised way. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Vector spaces

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Convex relaxations for binary image partitioning and perceptual grouping 23rd

引用

23rd German Association for pattern recognition Symposium, DAGM 2001

作者： Keuchel, Jens Schellewald, Christian Cremers, Daniel Schnörr, Christoph Computer Vision Graphics and Pattern Recognition Group Department of Mathematics and Computer Science University of Mannheim MannheimD-68131 Germany

ISBN: (纸本)3540425969

We consider approaches to computer vision problems which require the minimization of a global energy functional over binary variables and take into account both local similarity and spatial context. The combinatorial nature of such problems has lead to the design of various approximation algorithms in the past which often involve tuning parameters and tend to get trapped in local minima. In this context, we present a novel approach to the field of computer vision that amounts to solving a convex relaxation of the original problem without introducing any additional parameters. Numerical ground truth experiments reveal a relative error of the convex minimizer with respect to the global optimum of below 2% on the average. We apply our approach by discussing two specific problem instances related to image partitioning and perceptual grouping. Numerical experiments illustrate the quality of the approach which, in the partitioning case, compares favorably with established approaches like the ICM-algorithm. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Approximation algorithms

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On-ine variational estimation of dynamical fluid flows with physics-based spatio-temporal regularization

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28th Symposium of the German Association for pattern recognition, DAGM 2006

作者： Ruhnau, Paul Stahl, Annette Schnörr, Christoph Computer Vision Graphics and Pattern Recognition Group Department of Mathematics and Computer Science University of Mannheim D-68131 Mannheim Germany

ISBN: (纸本)3540444122

We present a variational approach to motion estimation of instationary fluid flows. Our approach extends prior work along two directions;(i) The full incompressible Navier-Stokes equation is employed in order to obtain a physically consistent regularization which does not suppress turbulent flow variations, (ii) Regularization along the time-axis is employed as well, but formulated in a receding horizon manner contrary to previous approaches to spatio-temporal regularization. This allows for a recursive on-line (non-batch) implementation of our estimation framework. Ground-truth evaluations for simulated turbulent flows demonstrate that due to imposing both physical consistency and temporal coherency, the accuracy of flow estimation compares favourably even with optical flow approaches based on higher-order div-curl regularization. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Flow of fluids

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Motion competition: Variational integration of motion segmentation and shape regularization

Motion competition: Variational integration of motion segmen...

引用

24th German Association for pattern recognition Symposium, DAGM 2002

作者： Cremers, Daniel Schnörr, Christoph Computer Vision Graphics and Pattern Recognition Group Department of Mathematics and Computer Science University of Mannheim MannheimD–68131 Germany

ISBN: (纸本)354044209X

We present a variational method for the segmentation of piecewise affine flow fields. Compared to other approaches to motion segmentation, we minimize a single energy functional both with respect to the affine motion models in the separate regions and with respect to the shape of the separating contour. In the manner of region competition, the evolution of the segmenting contour is driven by a force which aims at maximizing a homogeneity measure with respect to the estimated motion in the adjoining regions. We compare segmentations obtained for the models of piecewise affine motion, piecewise constant motion, and piecewise constant intensity. For objects which cannot be discriminated from the background by their appearance, the desired motion segmentation is obtained, although the corresponding segmentation based on image intensities fails. The region– based formulation facilitates convergence of the contour from its initialization over fairly large distances, and the estimated discontinuous flow field is progressively improved during the gradient descent minimization. By including in the variational method a statistical shape prior, the contour evolution is restricted to a subspace of familiar shapes, such that a robust estimation of irregularly moving shapes becomes feasible. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Flow fields

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Evaluation of convex optimization techniques for the weighted graph-matching problem in computer vision

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23rd German Association for pattern recognition Symposium, DAGM 2001

作者： Schellewald, Christian Roth, Stefan Schnörr, Christoph Computer Vision Graphics and Pattern Recognition Group Dept Mathematics and Computer Science University of Mannheim MannheimD-68131 Germany

ISBN: (纸本)3540425969

We present a novel approach to the weighted graph-matching problem in computer vision, based on a convex relaxation of the underlying combinatorial optimization problem. The approach always computes a lower bound of the objective function, which is a favorable property in the context of exact search algorithms. Furthermore, no tuning parameters have to be selected by the user, due to the convexity of the relaxed problem formulation. For comparison, we implemented a recently published deterministic annealing approach and conducted numerous experiments for both established benchmark experiments from combinatorial mathematics, and for random ground-truth experiments using computer-generated graphs. Our results show similar performance for both approaches. In contrast to the convex approach, however, four parameters have to be determined by hand for the annealing algorithm to become competitive. © Springer-Verlag Berlin Heidelberg 2001.

关键词： computer vision

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Human-focused computer vision applications

Human-focused computer vision applications

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International Conference on computer Graphics, Imaging and Visualisation, CGIV'06

作者： Piccardi, Massimo Department of Computer Systems Faculty of IT University of Technology Sydney Australia UTS Computer Vision Research Group IEEE IEEE Computer Society International Association for Pattern Recognition

ISBN: (纸本)0769526063

Recent years have seen an increasing number of computer vision applications focusing on humans as their objects of interest. Such applications include video surveillance, domotics, multimedia semantic annotation and indexing, human-computer interfaces, affective computing, just to cite a few. What exactly are their "objects of interest"? A broad range of human-related features: motion, gestures, actions, interactions, activities, attitudes, behaviours, identity. This keynote will offer a survey of this field and present some current work from the speaker and his collaborators in the areas of emotion recognition and people tracking within camera networks. © 2006 IEEE.

关键词： computer vision

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Warp that smile on your face: Optimal and smooth deformations for face recognition

Warp that smile on your face: Optimal and smooth deformation...

引用

作者： Gass, Tobias Pishchulin, Leonid Dreuw, Philippe Ney, Hermann Computer Vision Laboratory ETH Zurich Switzerland Computer Vision and Multimodal Computing MPI Informatics Saarbruecken Germany Human Language Technology and Pattern Recognition Group RWTH Aachen University Germany

ISBN: (纸本)9781424491407

In this work, we present novel warping algorithms for full 2D pixel-grid deformations for face recognition. Due to high variation in face appearance, face recognition is considered a very difficult task, especially if only a single reference image, for example a mug-shot, per face is available. Usually model-based approaches with additional training data are used to cope with several types of variation occurring in facial imaging. Image warping contrarily yields a distance measure which is invariant with regard to several types of variation. This allows for precise recognition even using only very few reference observations. Due to the computationally complex problem of optimal 2D warping, pseudo-2D warping-based approaches in the past represented strong approximations of the original problem, and were mainly successful on data with low variability or rectified images. We propose a novel 2D warping method which is globally optimal and makes no prior assumtions on the data variability besides two-dimensional smootheness constraints which both avoid local mirroring and gaps and significantly speed up the optimization. Furthermore, we show that occlusion handling is imperative to obtain smooth warpings in a variety of domains. We evaluate our novel algorithm on various well known databases, such as the AR-Face and CMU-PIE database, and provide a detailed comparison to existing warping approaches. We show that by using simple relative 2D constraints, strong local features and a kernel, which is robust w.r.t. occlusions, our computationally complex approaches outperform state-of-the-art results for recognizing faces under varying expressions, occlusions and poses. Most interestingly, we achieve higher accuracy using fewer training instances per class compared to methods learning a model of the 3D shape. © 2011 IEEE.

关键词： Face recognition

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