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共 467 条记录，以下是381-390 订阅

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EEG Subspace Representations and Feature Selection for Brain-computer Interfaces

EEG Subspace Representations and Feature Selection for Brain...

引用

conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Anderson, Charles W. Kirby, Michael J. Department of Computer Science Colorado State University Fort CollinsCO80523 United States Department of Mathematics Colorado State University Fort CollinsCO80523 United States

ISBN: (纸本)0769519008

Electroencephalogram (EEG) signals recorded from a persons scalp have been used to control binary cursor movements. Multiple choice paradigms will require more sophisticated protocols involving multiple mental tasks and signal representations that capture discriminatory characteristics of the EEG signals. In this study, six-channel EEG is recorded from a subject performing two mental tasks. The signals are transformed via the Karhunen-Loéve or maximum noise fraction transformations and classified by quadratic discriminant analysis. In addition, classification accuracy is tested for all subsets of the six EEG channels. Best results are approximately 90% correct when training and testing data are recorded on the same day and 75% correct when training and testing data are recorded on different days. © 2003 IEEE.

关键词： Electroencephalography

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Parametric Subpixel Matchpoint Recovery with Uncertainty Estimation: A Statistical Approach

Parametric Subpixel Matchpoint Recovery with Uncertainty Est...

引用

conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Steele, Matt Jaynes, Christopher Department of Computer Science University of Kentucky LexingtonKY40513 United States

ISBN: (纸本)0769519008

We present a novel matchpoint acquisition method capable of producing accurate correspondences at subpixel precision. Given the known representation of the point to be matched, such as a projected fiducial in a structured light system, the method estimates the fiducial location and its expected uncertainty. Improved matchpoint precision has application in a number of calibration tasks, and uncertainty estimates can be used to significantly improve overall calibration results. A simple parametric model captures the relationship between the known fiducial and its corresponding position, shape, and intensity on the image plane. For each match-point pair, these unknown model parameters are recovered using maximum likelihood estimation to determine a sub-pixel center for the fiducial. The uncertainty of the match-point center is estimated by performing forward error analysis on the expected image noise. Uncertainty estimates used in conjunction with the accurate matchpoints can improve calibration accuracy for multi-view systems. © 2003 IEEE.

关键词： Calibration

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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

conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Xiong, Yingen Quek, Francis Wright State University Department of Computer Science and Engineering 3640 Colonel Hwy DaytonOH45435 United States

ISBN: (纸本)0769519008

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. © 2003 IEEE.

关键词： Palmprint recognition

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Noise Adaptive Channel Smoothing of Low-Dose Images

Noise Adaptive Channel Smoothing of Low-Dose Images

引用

conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Scharr, Hanno Felsberg, Michael Forssén, Per-Erik Intel Research 2200 Mission College Blvd. Santa ClaraCA95054 United States Computer Vision Laboratory Linköping University Linköping581 83 Sweden

ISBN: (纸本)0769519008

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. © 2003 IEEE.

关键词： Diffusion

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Statistical Search for Hierarchical Linear Optimal Representations of Images

Statistical Search for Hierarchical Linear Optimal Represent...

引用

conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Zhang, Qiang Liu, Xiuwen Srivastava, Anuj Department of Computer Science Florida State University TallahasseeFL32306-4530 United States Department of Statistics Florida State University TallahasseeFL32306 United States

ISBN: (纸本)0769519008

Although linear representations of images are widely used in appearance-based recognition of objects, the frequently used ideas, such as PCA, ICA, and FDA, are often found to be suboptimal. A stochastic search algorithm has been proposed recently [4] for finding representations that are optimal for specific tasks and datasets. However, this search algorithm is computationally efficient only when the image size is relatively small. Here we propose a hierarchical learning algorithm to speed up the search. The proposed approach decomposes the original optimization problem into several stages according to a hierarchical organization. In particular, the following idea is applied recursively: (i) reduce the image dimension using a shrinkage matrix, (ii) optimize the recognition performance in the reduced space, and (iii)expand the optimal subspace to the bigger space in a pre-specified way. We show that the optimal performance is maintained in the last step. By applying this decomposition procedure recursively, a hierarchy of layers is formed. This speeds up the original algorithm significantly since the search is performed mainly in reduced spaces. The effectiveness of hierarchical learning is illustrated on a popular database, where the computation time is reduced by a large factor compared to the original algorithm. © 2003 IEEE.

关键词： Learning algorithms

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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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conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Chen, Huimin Pattipati, Krishna Kirubarajan, Thiagalingam Bar-Shalom, Yaakov University of New Orleans Dept. of Electrical Engineering New OrleansLA70148 United States University of Connecticut Dept. of Electrical and Computer Eng. StorrsCT06269-2157 United States McMaster University Dept. of Electrical and Computer Eng. HamiltonON Canada

ISBN: (纸本)0769519008

In this paper we formulate data association with possibly unresolved measurements as an augmented assignment problem. 0Unlike 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. © 2003 IEEE.

关键词： Linear programming

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Application of Structured Illumination in Nano-Scale vision

Application of Structured Illumination in Nano-Scale Vision

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conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Ryu, J. Horn, B.K.P. Mermelstein, M.S. Hong, S. Freeman, D.M. Harvard-MIT Div. of Health Sci. and Tech. CambridgeMA United States Dep. of Elec. Eng. and Comp. Sci. MIT CambridgeMA United States Lightwave Instruments LLC WatertownMA United States

ISBN: (纸本)0769519008

We describe how structured illumination patterns can be used to increase the resolution of an imaging system for optical microscopy. A target is illuminated by a sequence of finely textured light patterns formed by the interference of multiple coherent beams. The sequence of brightness values reported from a single pixel of a CCD imager encodes the target contrast pattern with sub-pixel resolution. Fourier domain components at spatial frequencies contained in the probing illumination patterns can be recovered from the pixel brightness sequence by solving a set of over-determined linear equations. We show that uniform angular spacing of the beams generating the illumination patterns leads to less than ideal sampling of the transform space and we propose alternative geometric arrangements. We describe an image reconstruction algorithm based on the Voronoi diagram that applies when the transform domain is not sampled uniformly. Finally, the contrast patterns within individual pixels can be spliced together to forman image encompassing multiple pixels. © 2003 IEEE.

关键词： Pixels

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Direct Least Square Fitting of Paracatadioptric Line Images

Direct Least Square Fitting of Paracatadioptric Line Images

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conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Barreto, Joao P. Araujo, Helder Institute of Systems and Robotics Dept. of Electrical and Computer Engineering University of Coimbra Coimbra3030 Portugal

ISBN: (纸本)0769519008

Paracatadioptric sensors combine a parabolic shaped mirror and a camera inducing an orthographic projection. Such a configuration provides a wide field of view while keeping a single effective viewpoint. In general the paracatadioptric image of a line is a conic curve. The estimation of line images is an important subject for applications such as reconstruction and visual control of motion. However the estimation of the conic curves where lines are mapped is hard to accomplish. In general only a small arc of the conic is visible in the image and conventional conic fitting techniques are unable to correctly estimate the curve. This paper shows that line images can be accurately estimated by constraining the search space. A conic curve is the paracatadioptric image of a line if, and only if, the image of the circular points lie on the curve and two certain points are conjugate with respect to the conic. Considering the space of all conic curves, the line images lie in a linear subspace which depends on the system calibration. The paracatadioptric projection of a line can estimated by fitting a conic in the subspace to the data points. The proposed approach is computationally efficient since the fitting problem can be solved by an eigensystem. © 2003 IEEE.

关键词： Curve fitting

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A Study on Bayes Feature Fusion for Image Classification

A Study on Bayes Feature Fusion for Image Classification

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conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Shi, X. Manduchi, R. Department of Computer Engineering University of California Santa CruzCA United States

ISBN: (纸本)0769519008

We consider here the problem of image classification when more than one visual feature are available. In these cases, Bayes fusion offers an attractive solution by combining the results of different classifiers (one classifier per feature). This is a general form of the so-called "naive Bayes" approach. Analyzing the performance of Bayes fusion with respect to a Bayesian classifier over the joint feature distribution, however, is tricky. On the one hand, it is well-known that the latter has lower bias than the former, unless the features are conditionally independent, in which case the two coincide. On the other hand, as noted by Friedman, the low variance associated with naive Bayes estimation may dramatically mitigate the effect of its bias. In this paper, we attempt to assess the tradeoff between these two factors by means of experimental tests on two image data sets using color and texture features. Our results suggest that (1) the difference between the correct classification rates using Bayes fusion and using the joint feature distribution is a function of the conditional dependence of the features (measured in terms of mutual information), however: (2) for small training data size, Bayes fusion performs almost as well as the classifier on the joint distribution. © 2003 IEEE.

关键词： Image classification

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computer vision Algorithms for Quantifying the Growth and Behavior of Neurons Cultured on Nanofabricated Surfaces

Computer Vision Algorithms for Quantifying the Growth and Be...

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conference on computer vision and pattern recognition workshop, cvprw 2003

作者： Karim, Muhammad-Amri Abdul Al-Kofahi, Khalid Roysam, Badrinath Dowell-Mesfin, Natalie Hussain, Rifat J. Shain, William Turner, James N. Electrical Computer and Systems Engineering Dept. Rensselaer Polytechnic Institute TroyNY12180 United States Wadsworth Center New York State Department of Health AlbanyNY12201 United States

ISBN: (纸本)0769519008

Neuron growth on nanofabricated silicon surfaces, once understood, is fundamental to engineer circuits involving neurons and electronic components, leading to applications such as next-generation brain implants, and high-throughput neurologic drug screening assay systems. Precise quantification of neuronal growth and behavior from image samples requires computer vision algorithms for automatic tracing of neurons, and flexible algorithms for reliable registration and analysis of multi-fluorophore imagery. The tracing algorithms must be robust to high levels of clutter and common imaging artifacts, process discontinuities, and quantum noise, especially when live neurons are imaged. Finally, the large numbers of images that must be processed for a hypothesis test or assay call for computationally efficient algorithms. A fully automated neuron tracing algorithm based on the use of robust detection and estimation principles is described here that meets the above needs. It takes 2 seconds to trace and extract morphological statistics from a typical 1280 x 1024 image on a Pentium III, 1 GHz personal computer. It was validated against manually generated traces and the errors were in the range of 1-5% per image. © 2003 IEEE.

关键词： Neurons

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