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

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Resolving objects at higher resolution from a single motion-blurred image

Resolving objects at higher resolution from a single motion-...

引用

IEEE Conference on computer vision and pattern recognition

作者： Agrawal, Amit Raskar, Ramesh MERL 201 Broadway Cambridge MA 02139 USA

ISBN: (纸本)9781424411795

Motion blur can degrade the quality of images and is considered a nuisance for computer vision problems. In this paper, we show that motion blur can in-fact be used for increasing the resolution of a moving object. Our approach utilizes the information in a single motion-blurred image without any image priors or training images. As the blur size increases, the resolution of the moving object can be enhanced by a larger factor albeit with a corresponding increase in reconstruction noise. Traditionally, motion deblurring and super-resolution have been ill-posed problems. Using a coded-exposure camera that preserves high spatial frequencies in the blurred image, we present a linear algorithm for the combined problem of deblurring and resolution enhancement and analyze the invertibility of the resulting linear system. We also show a method to selectively enhance the resolution of a narrow region of high-frequency features, when the resolution of the entire moving object cannot be increased due to small motion blur Results on real images showing up to four times resolution enhancement are presented.

关键词： Image resolution Spatial resolution Degradation computer vision Image reconstruction Cameras Frequency Image analysis Algorithm design and analysis Linear systems

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OpenVL: Towards a novel software architecture for computer vision

OpenVL: Towards a novel software architecture for computer v...

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IEEE Conference on computer vision and pattern recognition

作者： Shen, Changsong Fels, Sidney S. Little, James J. Univ British Columbia Dept Elect & Comp Engn Vancouver BC V5Z 1M9 Canada Univ British Columbia Dept Comp Sci Vancouver BC Canada

ISBN: (纸本)9781424411795

This paper presents our progress on OpenVL - a novel software architecture to address efficiency through facilitating hardware acceleration, reusability and scalability for computer vision. A logical image understanding pipeline is introduced to allow parallel processing. As well, we discuss our middleware - VLUT that enables applications to operate transparently over a heterogeneous collection of hardware implementations. OpenVL works as a state machine, with an event-driven mechanism to provide users with application-level interaction. Various explicit or implicit synchronization and communication methods are supported among distributed processes in the logical pipelines. The intent of OpenVL is to allow users to quickly and easily recover useful information from multiple scenes across various software environments and hardware platforms. We implement two different human tracking systems to validate the critical underlying concepts of OpenVL.

关键词： Software architecture

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Optimizing distribution-based matching by random subsampling

Optimizing distribution-based matching by random subsampling

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IEEE Conference on computer vision and pattern recognition

作者： Leung, Alex Po Gong, Shaogang Queen Mary Univ London Dept Comp Sci Mile End Rd London E1 4NS England

ISBN: (纸本)9781424411795

We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probability that a candidate sampling distribution is a good approximation to the model distribution. The improvement is demonstrated with applications to object detection, Mean-Shift tracking using color distributions and tracking with improved robustness for low-resolution video sequences. The problem of minimizing the number of samples required for robust distribution matching is formulated as a constrained optimization problem with the specified probability as the objective function. We show that surprisingly Mean-Shift tracking using our method requires very few samples. Our experiments demonstrate that robust tracking can be achieved with even as few as S random samples from the distribution of the target candidate. This leads to a considerably reduced computational complexity that is also independent of object size. We show that random subsampling speeds up tracking by two orders of magnitude for typical object sizes.

关键词： pattern recognition

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Dynamic object recognition and tracking of mobile robot by monocular vision

Dynamic object recognition and tracking of mobile robot by m...

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5th International Symposium on Multispectral Image Processing and pattern recognition

作者： Liu, Lei Wang, Yongji Huazhong Univ Sci & Technol Dept Control Sci & Engn Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9780819469502

Monocular vision is widely used in mobile robot's motion control for its simple structure and easy using. An integrated description to distinguish and tracking the specified color targets dynamically and precisely by the Monocular vision based on the imaging principle is the major topic of the paper. The mainline is accordance with the mechanisms of visual processing strictly, including the pretreatment and recognition processes. Specially, the color models are utilized to decrease the influence of the illumination in the paper. Some applied algorithms based on the practical application are used for image segmentation and clustering. After recognizing the target, however the monocular camera can't get depth information directly, 3D Reconstruction Principle is used to calculate the distance and direction from robot to target. To emend monocular camera reading, the laser is used after vision measuring. At last, a vision servo system is designed to realize the robot's dynamic tracking to the moving target.

关键词： monocular vision Imaging principle image processes 3D reconstruction vision servo system

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Dimensionality reduction and clustering on statistical manifolds

Dimensionality reduction and clustering on statistical manif...

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IEEE Conference on computer vision and pattern recognition

作者： Lee, Sang-Mook Abbott, A. Lynn Ararnan, Philip A. Virginia Polytech Inst & State Univ Blacksburg VA 24061 USA US Forest Serv Southern Res Stn Blacksburg VA 24060 USA

ISBN: (纸本)9781424411795

Dimensionality reduction and clustering on statistical manifolds is presented. Statistical manifold [16] is a 2D Riemannian manifold which is statistically defined by maps that transform a parameter domain onto a set of probability density functions. Principal component analysis (PCA) based dimensionality reduction is performed on the manifold, and therefore, estimation of a mean and a variance of the set of probability distributions are needed. First, the probability distributions are transformed by an isometric transform that maps the distributions onto a surface of hyper-sphere. The sphere constructs a Riemannian manifold with a simple geodesic distance measure. Then, a Frechet mean is estimated on the Riemannian manifold to perform the PCA on a tangent plane to the mean. Experimental results show that clustering on the Riemannian space produce more accurate and stable classification than the one on Euclidean space.

关键词： computer vision

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Algorithms for batch matrix factorization with application to structure-from-motion

Algorithms for batch matrix factorization with application t...

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IEEE Conference on computer vision and pattern recognition

作者： Tardif, Jean-Philippe Bartoli, Adrien Trudeau, Martin Guilbert, Nicolas Roy, Sebastien Univ Montreal Montreal PQ H3C 3J7 Canada CNRS LASMEA Clermont Ferrand France Lund Univ Lund Sweden

ISBN: (纸本)9781424411795

Matrix factorization is a key component for solving several computer vision problems. It is particularly challenging in the presence of missing or erroneous data, which often arise in Structure-from-Motion. We propose batch algorithms for matrix factorization. They are based on closure and basis constraints, that are used either on the cameras or the structure, leading to four possible algorithms. The constraints are robustly computed from complete measurement sub-matrices with e.g. random data sampling. The cameras and 3D structure are then recovered through Linear Least Squares. Prior information about the scene such as identical camera positions or orientations, smooth camera trajectory, known 3D points and coplanarity of some 3D points can be directly incorporated. We demonstrate our algorithms on challenging image sequences with tracking error and more than 95% missing data.

关键词： computer vision

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An image-based approach for automatic detecting tasseling stage of maize using spatio-temporal saliency

An image-based approach for automatic detecting tasseling st...

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8th Symposium on Multispectral Image Processing and pattern recognition (mippr) - Remote Sensing Image Processing, Geographic Information Systems, and Other Applications

作者： Ye, Mengni Cao, Zhiguo Yu, Zhenghong Huazhong Univ Sci & Technol Sch Automat Natl Key Lab Sci & Tech Multispectral Informat Pr Wuhan 430074 Peoples R China

ISBN: (纸本)9780819498069

In this paper, we explored the application of computer vision technology to automatically detect the tasseling stage of maize. The commonly used HOG/SVM detection framework is chosen to recognize the ears of maize for determining the occurrence time of the stage. However, it cannot guarantee high precision rate. Thus, we proposed a new method called Spatio-temporal Saliency Mapping to highlight the ear while suppress the background, which significantly improve the detection performance. Comparing experiment has been carried out to testify the validity of our method and the results indicate that our method can meet the demand for practical observation.

关键词： Maize tasseling stage automatic detection technology computer vision spatio-temporal saliency map

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Recognizing night walkers based on one pseudoshape representation of gait

Recognizing night walkers based on one pseudoshape represent...

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IEEE Conference on computer vision and pattern recognition

作者： Tan, Daoliang Huang, Kaiqi Yu, Shiqi Tan, Tieniu Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100080 Peoples R China

ISBN: (纸本)9781424411795

Gait is a promising biometric cue which can facilitate the recognition of human beings, particularly when other biometrics are unavailable. Existing work for gait recognition, however, lays more emphasis on the problem of daytime walker recognition and overlooks the significance of walker recognition at night. This paper deals with the problem of recognizing nighttime walkers. We take advantage of infrared gait patterns to accomplish this task: 1) Walker detection is improved using intensity compensation-based background subtraction;2)pseudoshape-based features are proposed to describe gait patterns;3) the dimension of gait features is reduced through the principal component analysis (PCA) and linear discriminant analysis (LDA) techniques;4) temporal cues are exploited in the form of the relevant component analysis (RCA) learning;5) the nearest neighbor classifier is used to recognize unknown gait. Experimental results justify the effectiveness of our method and show that our method has an encouraging potential for the application in surveillance systems.

关键词： Gesture recognition

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Effective Gaussian mixture learning and shadow suppression for video foreground segmentation

Effective Gaussian mixture learning and shadow suppression f...

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5th International Symposium on Multispectral Image Processing and pattern recognition

作者： Wang, Yong Tian, Jinwen Tan, Yihua Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence State Key Lab Multi Spectral Informat Proc Techno Wuhan 430074 Peoples R China

ISBN: (纸本)9780819469502

Robust and efficient foreground segmentation is a crucial topic in many computer vision applications. In this paper, we propose an improved method of foreground segmentation with the Gaussian mixture model (GMM) for video surveillance. The number of mixture components of GMM is estimated according to the frequency of pixel value changes, the performance of GMM can be effectively enhanced with the modified background learning and update, new Gaussian distribution generation rule and shadow detection. In order to improve the efficiency, illumination assessment is used to decide whether there are shadows in the given image. Shadow suppression will be adopted based on morphological reconstruction. Besides, the detection of sudden illumination change and background updating are also presented. Results obtained with different real-world scenarios show the robustness and efficiency of the approach.

关键词： video segmentation background subtract mixture Gaussians model shadow removal

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Tabletop interaction system using plate position recognition by computer vision

Tabletop interaction system using plate position recognition...

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mippr 2009 - Automatic Target recognition and Image Analysis: 6th International Symposium on Multispectral Image Processing and pattern recognition

作者： Sakamoto, Kunio Takagi, Masahiro Faculty of Intelligence and Informatics Konan University 8-9-1 Okamoto Higashinada Kobe Hyogo 658-8501 Japan

ISBN: (纸本)9780819478061

The authors have researched an interactive media system using the augmented reality technology. The augmented reality system enhances user's perception and interaction with the real world. In this system, the object recognition and location registration is one of the most important aspects. We built a tabletop interaction system in which a player slides a tile as if he/she solves the 15-puzzle. The player moves the sliding tiles so as to connect lines as a virtual rail. The train runs along this line. The projector shoots the rail and scenery, taking the position of tile into consideration. To recognize tiles, we utilize a computer vision technology using a commercial connected USB camera. In this paper, we describe a tabletop interaction system with augmented reality. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Mixed reality

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