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检索条件"任意字段=MIPPR 2007: Pattern Recognition and Computer Vision"

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Incremental Linear Discriminant Analysis Using Sufficient Spanning Set Approximations

Incremental Linear Discriminant Analysis Using Sufficient Sp...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Tae-Kyun Kim Shu-Fai Wong Bjorn Stenger Josef Kittler Roberto Cipolla Department of Engineering University of Cambridge Cambridge UK Computer Vision Group Toshiba Research Europe Limited Cambridge UK CVSSP University of Surrey Guildford UK

This paper presents a new incremental learning solution for linear discriminant analysis (LDA). We apply the concept of the sufficient spanning set approximation in each update step, i.e. for the between-class scatter matrix, the projected data matrix as well as the total scatter matrix. The algorithm yields a more general and efficient solution to incremental LDA than previous methods. It also significantly reduces the computational complexity while providing a solution which closely agrees with the batch LDA result. The proposed algorithm has a time complexity of O(Nd 2 ) and requires O(Nd) space, where d is the reduced subspace dimension and N the data dimension. We show two applications of incremental LDA: First, the method is applied to semi-supervised learning by integrating it into an EM framework. Secondly, we apply it to the task of merging large databases which were collected during MPEG standardization for face image retrieval.

关键词： Linear discriminant analysis Light scattering Image retrieval Computational complexity Standardization MPEG 7 Standard Principal component analysis Europe computer vision Semisupervised learning

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Spatial selection for attentional visual tracking

Spatial selection for attentional visual tracking

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Conference on computer vision and pattern recognition (CVPR)

作者： Ming Yang Junsong Yuan Ying Wu EECS Department Northwestern University Evanston IL USA

Long-duration tracking of general targets is quite challenging for computer vision, because in practice target may undergo large uncertainties in its visual appearance and the unconstrained environments may be cluttered and distractive, although tracking has never been a challenge to the human visual system. Psychological and cognitive findings indicate that the human perception is attentional and selective, and both early attentional selection that may be innate and late attentional selection that may be learned are necessary for human visual tracking. This paper proposes a new visual tracking approach by reflecting some aspects of spatial selective attention, and presents a novel attentional visual tracking (AVT) algorithm. In AVT, the early selection process extracts a pool of attentional regions (ARs) that are defined as the salient image regions which have good localization properties, and the late selection process dynamically identifies a subset of discriminative attentional regions (D-ARs) through a discriminative learning on the historical data on the fly. The computationally demanding process of matching of the AR pool is done in an efficient and innovative way by using the idea in the locality-sensitive hashing (LSH) technique. The proposed AVT algorithm is general, robust and computationally efficient, as shown in extensive experiments on a large variety of real-world video.

关键词： Target tracking Humans Uncertainty computer vision Robustness Visual perception Psychology Data mining Motion estimation Visual system

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Combining local and global motion models for feature point tracking

Combining local and global motion models for feature point t...

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Conference on computer vision and pattern recognition (CVPR)

作者： Aeron Buchanan Andrew Fitzgibbon Department Engineering Science University of Oxford UK Microsoft Research Limited Cambridge UK

Accurate feature point tracks through long sequences are a valuable substrate for many computer vision applications, e.g. non-rigid body tracking, video segmentation, video matching, and even object recognition. Existing algorithms may be arranged along an axis indicating how global the motion model used to constrain tracks is. Local methods, such as the KLT tracker, depend on local models of feature appearance, and are easily distracted by occlusions, repeated structure, and image noise. This leads to short tracks, many of which are incorrect. Alone, these require considerable postprocessing to obtain a useful result. In restricted scenes, for example a rigid scene through which a camera is moving, such postprocessing can make use of global motion models to allow "guided matching " which yields long high-quality feature tracks. However, many scenes of interest contain multiple motions or significant non-rigid deformations which mean that guided matching cannot be applied. In this paper we propose a general amalgam of local and global models to improve tracking even in these difficult cases. By viewing rank-constrained tracking as a probabilistic model of 2D tracks rather than 3D motion, we obtain a strong, robust motion prior, derived from the global motion in the scene. The result is a simple and powerful prior whose strength is easily tuned, enabling its use in any existing tracking algorithm.

关键词： Tracking Layout Object recognition Karhunen-Loeve transforms Cameras computer vision Application software Image segmentation Robustness Motion pictures

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Breaking Visual CAPTCHAs with Naive pattern recognition Algorithms

Breaking Visual CAPTCHAs with Naive Pattern Recognition Algo...

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Annual computer Security Applications Conference

作者： Jeff Yan Ahmad Salah El Ahmad School of Computing Science Newcastle University UK UK Newcastle Univ. Newcastle upon Tyne

ISBN: (纸本)9780769530604;0769530605

Visual CAPTCHAs have been widely used across the Internet to defend against undesirable or malicious bot programs. In this paper, we document how we have broken most such visual schemes provided at ***, a publicly available web service for CAPTCHA generation. These schemes were effectively resistant to attacks conducted using a high-quality Optical Character recognition program, but were broken with a near 100% success rate by our novel attacks. In contrast to early work that relied on sophisticated computer vision or machine learning algorithms, we used simple pattern recognition algorithms but exploited fatal design errors that we discovered in each scheme. Surprisingly, our simple attacks can also break many other schemes deployed on the Internet at the time of writing: their design had similar errors. We also discuss defence against our attacks and new insights on the design of visual CAPTCHA schemes.

关键词： pattern recognition Internet Machine learning algorithms computer errors Web services Optical character recognition software Character recognition computer vision Algorithm design and analysis Writing

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Integrating Global and Local Structures: A Least Squares Framework for Dimensionality Reduction

Integrating Global and Local Structures: A Least Squares Fra...

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Conference on computer vision and pattern recognition (CVPR)

作者： Jianhui Chen Jieping Ye Qi Li Computer Science and Engineering Department Arizona State University USA Computer Science Department Western Kentucky University USA

Linear discriminant analysis (LDA) is a popular statistical approach for dimensionality reduction. LDA captures the global geometric structure of the data by simultaneously maximizing the between-class distance and minimizing the within-class distance. However, local geometric structure has recently been shown to be effective for dimensionality reduction. In this paper, a novel dimensionality reduction algorithm is proposed, which integrates both global and local structures. The main contributions of this paper include: (1) We present a least squares formulation for dimensionality reduction, which facilities the integration of global and local structures; (2) We design an efficient model selection scheme for the optimal integration, which balances the tradeoff between the global and local structures; and (3) We present a detailed theoretical analysis on the intrinsic relationship between the proposed framework and LDA. Our extensive experimental studies on benchmark data sets show that the proposed integration framework is competitive with traditional dimensionality reduction algorithms, which use global or local structure only.

关键词： Least squares methods Linear discriminant analysis Laplace equations Support vector machines computer science Application software Training data Machine learning algorithms Algorithm design and analysis computer vision

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Efficient Sampling of Disparity Space for Fast And Accurate Matching

Efficient Sampling of Disparity Space for Fast And Accurate ...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Jan Cech Radim Sara Center for Machine Perception Czech Technical University Prague Czech Republic

A simple stereo matching algorithm is proposed that visits only a small fraction of disparity space in order to find a semi-dense disparity map. It works by growing from a small set of correspondence seeds. Unlike in known seed-growing algorithms, it guarantees matching accuracy and correctness, even in the presence of repetitive patterns. This success is based on the fact it solves a global optimization task. The algorithm can recover from wrong initial seeds to the extent they can even be random. The quality of correspondence seeds influences computing time, not the quality of the final disparity map. We show that the proposed algorithm achieves similar results as an exhaustive disparity space search but it is two orders of magnitude faster. This is very unlike the existing growing algorithms which are fast but erroneous. Accurate matching on 2-megapixel images of complex scenes is routinely obtained in a few seconds on a common PC from a small number of seeds, without limiting the disparity search range.

关键词： Sampling methods Layout Statistics Pixel pattern matching Surface reconstruction Image reconstruction Pipelines Image segmentation Parameter estimation

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A Component-Based Approach to Hand Verification

A Component-Based Approach to Hand Verification

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Conference on computer vision and pattern recognition (CVPR)

作者： Gholamreza Amayeh George Bebis Ali Erol Mircea Nicolescu Computer Vision Laboratory University of Nevada Reno NV USA

This paper describes a novel hand-based verification system based on palm-finger segmentation and fusion. The proposed system operates on 2D hand images acquired by placing the hand on a planar lighting table without any guidance pegs. The segmentation of the palm and the fingers is performed without requiring the extraction of any landmark points on the hand. First, the hand is segmented from the forearm using a robust, iterative methodology based on morphological operators. Then, the hand is segmented into six regions corresponding to the palm and the fingers using morphological operators again. The geometry of each component of the hand is represented using high order Zernike moments which are computed using an efficient methodology. Finally, verification is performed by fusing information from different parts of the hand. The proposed system has been evaluated on a database of 101 subjects illustrating high accuracy and robustness. Comparisons with competitive approaches that use the whole hand illustrate the superiority of the proposed, component-based, approach both in terms of accuracy and robustness. Qualitative comparisons with state of the art systems illustrate that the proposed system has comparable or better performance.

关键词： Fingers Robustness Image segmentation Biometrics Shape Authentication Computational geometry Feature extraction Surface morphology Extremities

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A minimal solution to the autocalibration of radial distortion

A minimal solution to the autocalibration of radial distorti...

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Conference on computer vision and pattern recognition (CVPR)

作者： Zuzana Kukelova Tomas Pajdla Center for Machine Perception Department of Cybernetics Faculty of Elec. Engineering Czech Technical University Prague Czech Republic

Epipolar geometry and relative camera pose computation are examples of tasks which can be formulated as minimal problems and solved from a minimal number of image points. Finding the solution leads to solving systems of algebraic equations. Often, these systems are not trivial and therefore special algorithms have to be designed to achieve numerical robustness and computational efficiency. In this paper we provide a solution to the problem of estimating radial distortion and epipolar geometry from eight correspondences in two images. Unlike previous algorithms, which were able to solve the problem from nine correspondences only, we enforce the determinant of the fundamental matrix be zero. This leads to a system of eight quadratic and one cubic equation in nine variables. We simplify this system by eliminating six of these variables. Then, we solve the system by finding eigenvectors of an action matrix of a suitably chosen polynomial. We show how to construct the action matrix without computing complete Grobner basis, which provides an efficient and robust solver. The quality of the solver is demonstrated on synthetic and real data.

关键词： Equations Cameras Eigenvalues and eigenfunctions Robustness Polynomials Cybernetics Computational geometry Algorithm design and analysis Computational efficiency computer vision

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Extraction of surface normal and index of refraction using a pair of passive infrared polarimetric sensors

Extraction of surface normal and index of refraction using a...

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Conference on computer vision and pattern recognition (CVPR)

作者： Firooz Sadjadi Farzad Sadjadi Lockheed Martin Corporation Saint Paul Minnesota Department of Physics and Astronomy University of Minnesota Minneapolis Minnesota

This paper summarizes a method for extracting 3D information and indices of refraction from a scene by means of a pair of polarimetric passive imaging sensors. Each sensor provides the Stokes vector at each sensor pixel location, from which, degree and angle of linear polarization are computed. Angle of linear polarization provides the azimuth angle of the surface normal vector. Two cases are considered. For the special case when the two sensors have a common azimuth plane the index of refraction can be find analytically in terms of the degrees of polarization and the angle between the lines of sight from the two sensors, from which the depression angle of the surface normal can be computed. For the second and more general case the surface normal is estimated from the cross-product of the azimuth vectors from the two sensors and the inner product of the line of sight vectors and surface normal. Once the de-presion angles are estimated the index of refraction can be computed.

关键词： Infrared sensors Electromagnetic wave polarization Optical surface waves Electromagnetic refraction Azimuth Infrared image sensors Optical imaging computer vision Geometry Surface waves

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Improving Part based Object Detection by Unsupervised, Online Boosting

Improving Part based Object Detection by Unsupervised, Onlin...

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Conference on computer vision and pattern recognition (CVPR)

作者： Bo Wu Ram Nevatia Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA

Detection of objects of a given class is important for many applications. However it is difficult to learn a general detector with high detection rate as well as low false alarm rate. Especially, the labor needed for manually labeling a huge training sample set is usually not affordable. We propose an unsupervised, incremental learning approach based on online boosting to improve the performance on special applications of a set of general part detectors, which are learned from a small amount of labeled data and have moderate accuracy. Our oracle for unsupervised learning, which has high precision, is based on a combination of a set of shape based part detectors learned by off-line boosting. Our online boosting algorithm, which is designed for cascade structure detector, is able to adapt the simple features, the base classifiers, the cascade decision strategy, and the complexity of the cascade automatically to the special application. We integrate two noise restraining strategies in both the oracle and the online learner. The system is evaluated on two public video corpora.

关键词： Object detection Boosting Detectors Labeling Intelligent robots Motion segmentation computer vision Surveillance Face detection Intelligent systems

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