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检索条件"任意字段=2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005"

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Acoustic feature combination for robust speech recognition

Acoustic feature combination for robust speech recognition

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2005 ieee International conference on Acoustics, Speech, and Signal Processing, ICASSP '05

作者： Zolnay, András Schlüter, Ralf Ney, Hermann Computer Science Department Human Language Technology and Pattern Recognition RWTH Aachen University 52056 Aachen Germany

ISBN: (纸本)0780388747

In this paper, we consider the use of multiple acoustic features of the speech signal for robust speech recognition. We investigate the combination of various auditory based (Mel Frequency Cepstrum Coefficients, Perceptual Linear Prediction, etc.) and articulatory based (voicedness) features. Features are combined by a Linear Discriminant Analysis based and by a log-linear model combination based techniques. We describe the two feature combination techniques and compare the experimental results. Experiments performed on the large-vocabulary task VerbMobil II (German conversational speech) show that the accuracy of automatic speech recognition systems can be improved by the combination of different acoustic features. © 2005 ieee.

关键词： Feature extraction

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3D Measurements in Cargo Inspection with a Gamma-Ray Linear Pushbroom Stereo System

3D Measurements in Cargo Inspection with a Gamma-Ray Linear ...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Zhigang Zhu Li Zhao Jiayan Lei Department of Computer Science The City College City University of New York NY USA

In this paper we present a practical approach for 3D measurements in gamma-ray (or X-ray) cargo inspection. The linear pushbroom sensor model is used for such a gamma-ray scanning system. Thanks to the constraints of the real scanning system, we model the system by using a linear pushbroom model with only one rotation angle instead of three. This greatly simplifies the calibration procedure and increases the robustness of the parameter estimation. Using only the knowledge of the dimensions of a cargo container, we automatically calibrate the sensor and find all the sensor parameters, including the image center, the focal length, the 3D sensor starting location, the viewing direction, and the scanning speed. Then, a semi-automated stereo reconstruction approach is proposed to obtain 3D measurements of objects inside the cargo by using two such scanning systems with different scanning angles to construct a pushbroom stereo system. Experimental results of 3D measurements and visualization of a 3D cargo container and the objects inside are presented. With both the interactive matching procedure and the 3D visualization interface, the 3D measurements could add more value to today’s cargo inspection systems.

关键词： Inspection Image sensors Containers Stereo image processing Visualization Sensor systems Gamma ray detectors Calibration Robustness Parameter estimation

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Performance analysis of iris based identification system at the matching score level

Performance analysis of iris based identification system at ...

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2005 ieee International conference on Acoustics, Speech, and Signal Processing, ICASSP '05

作者： Schmid, N.A. Cukic, B. Ketkar, M. Singh, H. Lane Department of Computer Science and Electrical Engineering West Virginia University Morgantown WV 26506 Department of Statistics West Virginia University Morgantown WV 26506

ISBN: (纸本)0780388747

We analyze the performance of an iris based recognition system. We consider a practical setting where matching scores are accessible for collecting data. We assume that multiple scans from the same iris are available and design the decision rules based on this assumption. We show that vectors of matching scores are described by a Gaussian model with dependent components both under the Genuine and Imposter hypotheses. Two test statistics: the average Hamming distance and the log-likelihood ratio are designed. We show that the log-likelihood ratio with well estimated maximum likelihood parameters in it outperforms the first test statistic. We further use empirical approach, Chernoff bound, and Large Deviations approach to predict the performance of the recognition system. © 2005 ieee.

关键词： pattern recognition

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A Combinational Approach to the Fusion, De-noising and Enhancement of Dual-Energy X-Ray Luggage Images

A Combinational Approach to the Fusion, De-noising and Enhan...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Zhiyu Chen Yue Zheng B.R. Abidi D.L. Page M.A. Abidi Imaging Robotics and Intelligent Systems Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

X-ray luggage inspection systems play an important role in ensuring air travelers’ security. However, the false alarm rate of commercial systems can be as high as 20% due to less than perfect image processing algorithms. In an effort to reduce the false alarm rate, this paper proposes a combinational scheme to fuse, de-noise and enhance dual-energy X-ray images for better object classification and threat detection. The fusion step is based on the wavelet transform. Fused images generally reveal more detail information; however, background noise often gets amplified during the fusion process. This paper applies a backgroundsubtraction- based noise reduction technique which is very efficient in removing background noise from fused X-ray images. The de-noised image is then processed using a new enhancement technique to reconstruct the final image. The final image not only contains complementary information from both source images, but is also background-noise-free and contrastenhanced, therefore easier to segment automatically or be interpreted by screeners, thus reducing the false alarm rate in X-ray luggage inspection.

关键词： Noise reduction X-ray imaging Inspection Background noise Security Image processing Fuses Object detection X-ray detection X-ray detectors

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A novel algorithm for fitting 3-D active appearance models: Applications to cardiac MRI segmentation

A novel algorithm for fitting 3-D active appearance models: ...

引用

14th Scandinavian conference on Image Analysis, SCIA 2005

作者： Andreopoulos, Alexander Tsotsos, John K. York University Dept. of Computer Science and Engineering Centre for Vision Research Toronto Ont. M3J 1P3 Canada

We present an efficient algorithm for fitting three dimensional (3-D) Active Appearance Models (AAMs). We do so, by introducing a 3-D extension of a recently proposed method that is based on the inverse compositional image alignment algorithm. We demonstrate its applicability for the segmentation of the left ventricle in short axis cardiac MRI. We perform experiments to evaluate the speed and segmentation accuracy of our algorithm on a total of 1473 cardiac MR images acquired from 11 patients. The fitting is around 60 times faster than standard Gauss-Newton optimization, with a segmentation accuracy that is as good as, and often better than Gauss-Newton. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Algorithms

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The radial trifocal tensor: a tool for calibrating the radial distortion of wide-angle cameras

The radial trifocal tensor: a tool for calibrating the radia...

引用

conference on computer vision and pattern recognition (cvpr)

作者： S. Thirthala M. Pollefeys Department of Computer Science UNC Chapel Hill USA

We present a technique to linearly estimate the radial distortion of a wide-angle lens given three views of a real-world plane. The approach can also be used with pure rotation as in this case all points appear as lying on a plane. The three views can even be recorded using three different cameras as long as the deviation from the pin-hole model for each camera is distortion along radial lines. We introduce the 1D radial camera which projects scene points onto radial lines and the radial trifocal tensor which encodes the multi-view relations between radial lines. Given at least seven triplets of corresponding points the radial trifocal tensor can be computed linearly. This allows recovery of the radial cameras and the projective reconstruction of the plane up to a two fold ambiguity. This 2D reconstruction is unaffected by radial distortion and can be used in different ways to compute the radial distortion parameters. We propose to use the division model as in this case we obtain a linear algorithm that computes the radial distortion coefficients and the 3 remaining degrees of freedom of the homography relating the reconstructed 2D plane to the undistorted image. Each feature point that has at least one corresponding point yields one linear constraint on those unknowns. Our method is validated on real-world images. We successfully calibrate several wide-angle cameras.

关键词： Tensile stress Cameras Nonlinear distortion Calibration Lenses Layout Image reconstruction computer vision computer science Mirrors

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Efficient mean-shift tracking via a new similarity measure

Efficient mean-shift tracking via a new similarity measure

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conference on computer vision and pattern recognition (cvpr)

作者： Changjiang Yang R. Duraiswami L. Davis Department of Computer Science Perceptual Interfaces and Reality Laboratory University of Maryland College Park MD USA

The mean shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. It finds local minima of a similarity measure between the color histograms or kernel density estimates of the model and target image. The most typically used similarity measures are the Bhattacharyya coefficient or the Kullback-Leibler divergence. In practice, these approaches face three difficulties. First, the spatial information of the target is lost when the color histogram is employed, which precludes the application of more elaborate motion models. Second, the classical similarity measures are not very discriminative. Third, the sample-based classical similarity measures require a calculation that is quadratic in the number of samples, making real-time performance difficult. To deal with these difficulties we propose a new, simple-to-compute and more discriminative similarity measure in spatial-feature spaces. The new similarity measure allows the mean shift algorithm to track more general motion models in an integrated way. To reduce the complexity of the computation to linear order we employ the recently proposed improved fast Gauss transform. This leads to a very efficient and robust nonparametric spatial-feature tracking algorithm. The algorithm is tested on several image sequences and shown to achieve robust and reliable frame-rate tracking.

关键词： Robustness Target tracking Histograms Density measurement Kernel Extraterrestrial measurements Motion measurement Gaussian processes Testing Image sequences

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Discriminative density propagation for 3D human motion estimation

Discriminative density propagation for 3D human motion estim...

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conference on computer vision and pattern recognition (cvpr)

作者： C. Sminchisescu A. Kanaujia Zhiguo Li D. Metaxas Department of Computer Science University of Toronto Canada Department of Computer Science Rutgers University USA

We describe a mixture density propagation algorithm to estimate 3D human motion in monocular video sequences based on observations encoding the appearance of image silhouettes. Our approach is discriminative rather than generative, therefore it does not require the probabilistic inversion of a predictive observation model. Instead, it uses a large human motion capture data-base and a 3D computer graphics human model in order to synthesize training pairs of typical human configurations together with their realistically rendered 2D silhouettes. These are used to directly learn to predict the conditional state distributions required for 3D body pose tracking and thus avoid using the generative 3D model for inference (the learned discriminative predictors can also be used, complementary, as importance samplers in order to improve mixing or initialize generative inference algorithms). We aim for probabilistically motivated tracking algorithms and for models that can represent complex multivalued mappings common in inverse, uncertain perception inferences. Our paper has three contributions: (1) we establish the density propagation rules for discriminative inference in continuous, temporal chain models; (2) we propose flexible algorithms for learning multimodal state distributions based on compact, conditional Bayesian mixture of experts models; and (3) we demonstrate the algorithms empirically on real and motion capture-based test sequences and compare against nearest-neighbor and regression methods.

关键词： Humans Motion estimation Inference algorithms Biological system modeling Predictive models Video sequences Image coding computer graphics Rendering (computer graphics) Bayesian methods

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Level set evolution without re-initialization: a new variational formulation

Level set evolution without re-initialization: a new variati...

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conference on computer vision and pattern recognition (cvpr)

作者： Chunming Li Chenyang Xu Changfeng Gui M.D. Fox Department of Electrical and Computer Engineering University of Connecticut Storrs CT USA Department of Imaging and Visualiza Siemens Corporate Research Inc. Princeton NJ USA Department of Mathematics University of Connecticut Storrs CT USA

In this paper, we present a new variational formulation for geometric active contours that forces the level set function to be close to a signed distance function, and therefore completely eliminates the need of the costly re-initialization procedure. Our variational formulation consists of an internal energy term that penalizes the deviation of the level set function from a signed distance function, and an external energy term that drives the motion of the zero level set toward the desired image features, such as object boundaries. The resulting evolution of the level set function is the gradient flow that minimizes the overall energy functional. The proposed variational level set formulation has three main advantages over the traditional level set formulations. First, a significantly larger time step can be used for numerically solving the evolution partial differential equation, and therefore speeds up the curve evolution. Second, the level set function can be initialized with general functions that are more efficient to construct and easier to use in practice than the widely used signed distance function. Third, the level set evolution in our formulation can be easily implemented by simple finite difference scheme and is computationally more efficient. The proposed algorithm has been applied to both simulated and real images with promising results.

关键词： Level set Active contours Solid modeling Computed tomography Partial differential equations Image segmentation computer vision Lagrangian functions Mathematics Data visualization

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Iris recognition based on adjustable scale wavelet transform

Iris recognition based on adjustable scale wavelet transform

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2005 27th Annual International conference of the Engineering in Medicine and Biology society, ieee-EMBS 2005

作者： Huang, Huifang Hu, Guangshu Department of Biomedical Engineering School of Medicine Tsinghua University Beijing China Department of Biomedical Engineering School of Computer and Information Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)0780387406

This paper represents a new method for iris recognition using the bandpass characteristic of wavelets and wavelet transform principles for detecting singularities. The iris image texture is divided into eight bands, and each band is processed to generate a 1-D intensity signal. The appropriate scale wavelet is used to filter each signal for quantization to 256 byte iris feature codes. Then the Hamming distance is adopted to match two iris codes. In particular, the appropriate scale for each signal is searched for by minimizing the Hamming distance. The results show that the performance of this method is better than some algorithms. Meanwhile, it is translation, rotation, and scale invariant, so it is promising to be used in a personal identification system. © 2005 ieee.

关键词： pattern recognition

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