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检索条件"任意字段=2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010"

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Contrast enhancement of multi-displays using human contrast sensitivity

Contrast enhancement of multi-displays using human contrast ...

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conference on computer vision and pattern recognition (cvpr)

作者： A. Majumder Department of Computer Science University of California Irvine USA

Study of contrast sensitivity of the human eye shows that we are more sensitive to brightness differences at low intensity levels than at high intensity levels. We apply this fact effectively to achieve brightness seamless-ness in multi-projector displays. Multi-displays, popularly made of a rectangular array of partially overlapping projectors, show severe spatial variation in brightness. Existing methods achieve brightness uniformity across the display by matching the brightness response of every pixel to the pixel with the most limited contrast leading to severe compression in the contrast of the display. In this paper, we propose a method that allows a constrained variation in brightness guided by the human contrast sensitivity function such that it is imperceptible to the human eye. This achieves a seamless multi-display with a dramatic improvement in the contrast making the display practically usable.

关键词： Humans Brightness Liquid crystal displays Optical attenuators Optical filters Optical sensors computer science computer displays Large-scale systems Visualization

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Research on the constraint in SIFT point matching

Research on the constraint in SIFT point matching

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2nd International conference on Information Science and Engineering, ICISE2010

作者： Li, Xiangru Wang, Yongjun Lu, Yu School of Mathematical Sciences South China Normal University Guangzhou 510631 China

ISBN: (纸本)9781424480968

Establishing reliable point correspondences between two images is a fundamental problem in computer vision. This work focus on the evaluation of candidate correspondences in matching points based on SIFT features, which is one of the most popular local descriptor of feature points. We introduced a novel concept of ambiguity measure (AM), and proposed several AMs based on study of the typical "distance ratio between the nearest neighbor and the second". We also studied the AMs theoretically and experimentally. It is shown that the capacity of AM depends on whether the matching degree between the putative correspondence points are included in AM effectively. This research are helpful both for understanding the available method NNDR, and for designing more effective methods. © 2010 ieee.

关键词： pattern recognition

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Positional estimation of a mobile robot using edge visibility regions

Positional estimation of a mobile robot using edge visibilit...

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conference on computer vision and pattern recognition (cvpr)

作者： R. Talluri J.K. Aggarwal Computer and Vision Research Center University of Texas Austin Austin TX USA

A technique is presented for estimating the position and pose of an autonomous mobile robot navigating in an outdoor, urban environment consisting of polyhedral buildings. The 3-D description of the roof tops of the buildings are assumed to be given as a world model. A discussion is presented of the uses of an intermediate representation of the environment, called the edge visibility regions (EVRs), in the positional estimation process.< >

关键词： Mobile robots Robot kinematics Cameras Robot vision systems Navigation Robot sensing systems Orbital robotics computer vision Feature extraction Image sensors

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Counting Crowded Moving Objects

Counting Crowded Moving Objects

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conference on computer vision and pattern recognition (cvpr)

作者： V. Rabaud S. Belongie Department of Computer Science and Engineering University of California San Diego USA

In its full generality, motion analysis of crowded objects necessitates recognition and segmentation of each moving entity. The difficulty of these tasks increases considerably with occlusions and therefore with crowding. When the objects are constrained to be of the same kind, however, partitioning of densely crowded semi-rigid objects can be accomplished by means of clustering tracked feature points. We base our approach on a highly parallelized version of the KLT tracker in order to process the video into a set of feature trajectories. While such a set of trajectories provides a substrate for motion analysis, their unequal lengths and fragmented nature present difficulties for subsequent processing. To address this, we propose a simple means of spatially and temporally conditioning the trajectories. Given this representation, we integrate it with a learned object descriptor to achieve a segmentation of the constituent motions. We present experimental results for the problem of estimating the number of moving objects in a dense crowd as a function of time.

关键词： computer vision Motion segmentation Motion analysis Karhunen-Loeve transforms Trajectory Image motion analysis Optical computing computer science Humans Animals

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Image Denoising Via Learned Dictionaries and Sparse representation

Image Denoising Via Learned Dictionaries and Sparse represen...

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conference on computer vision and pattern recognition (cvpr)

作者： M. Elad M. Aharon Department of Computer Science Technion-Israel Institute of Technology Haifa Israel

We address the image denoising problem, where zeromean white and homogeneous Gaussian additive noise should be removed from a given image. The approach taken is based on sparse and redundant representations over a trained dictionary. The proposed algorithm denoises the image, while simultaneously trainining a dictionary on its (corrupted) content using the K-SVD algorithm. As the dictionary training algorithm is limited in handling small image patches, we extend its deployment to arbitrary image sizes by defining a global image prior that forces sparsity over patches in every location in the image. We show how such Bayesian treatment leads to a simple and effective denoising algorithm, with state-of-the-art performance, equivalent and sometimes surpassing recently published leading alternative denoising methods.

关键词： Image denoising Dictionaries Noise reduction Additive noise Bayesian methods computer science Noise measurement Gaussian noise Measurement standards Algorithm design and analysis

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Imaging quality based state switch algorithm for outdoor moving robot system

Imaging quality based state switch algorithm for outdoor mov...

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2010 ieee International conference on Information and Automation, ICIA 2010

作者： Liu, Haoting Zhu, Hongwei Xu, Fenggang Lu, Hanqing National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences China Laboratory of System Usability Evaluation Department of Space Ergonomics Astronaut Research and Training Center of China

ISBN: (纸本)9781424457021

vision based computation of the moving CCD camera in an outdoor environment is one of the most difficult tasks in the computer vision (CV) research field. Currently, to implement only one CV function steadily, one even needs to develop a series of algorithms to meet the computational requirement of the complex environment change inevitably. So the choice of the switch occasion of these different algorithms for an abrupt change of the imaging definition is a problem. In this paper, we propose to use the Image Quality (IQ) as a measurement to find proper switch occasions of different CV algorithms for the outdoor robot system. Firstly we define three IQ metrics to describe the imaging definition of a CCD camera. Then we present an ARMA-ARCH model based multiple flows method to detect the abrupt change of these series. Finally, we use our method to cut the image sequence into multiple segments, which are fit to be processed by different CV algorithms. Many experiment results have shown the validity of our method. ©2010 ieee.

关键词： Image quality

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Shape Representation based on Integral Kernels: Application to Image Matching and Segmentation

Shape Representation based on Integral Kernels: Application ...

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conference on computer vision and pattern recognition (cvpr)

作者： Byung-Woo Hong E. Prados S. Soatto L. Vese University of California Los Angeles CA USA

This paper presents a shape representation and a variational framework for the construction of diffeomorphisms that establish "meaningful"correspondences between images, in that they preserve the local geometry of singularities such as region boundaries. At the same time, the shape representation allows enforcing shape information locally in determining such region boundaries. Our representation is based on a kernel descriptor that characterizes local shape. This shape descriptor is robust to noise and forms a scale-space in which an appropriate scale can be chosen depending on the size of features of interest in the scene. In order to preserve local shape during the matching procedure, we introduce a novel constraint to traditional energybased approaches to estimate diffeomorphic deformations, and enforce it in a variational framework.

关键词： Shape Kernel Image matching Image segmentation Noise shaping computer vision Geometry Noise robustness Layout Anatomical structure

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Face detection in complex background based on skin color features and improved AdaBoost algorithms

Face detection in complex background based on skin color fea...

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ieee International conference on Progress in Informatics and Computing (PIC)

作者： Li, Zhengming Xue, Lijie Tan, Fei School of Electrical and Information Engineering Jiangsu University Zhenjiang China

ISBN: (纸本)9781424467860

Face detection is a very hot topic in research application of pattern recognition and computer vision. It is widely applied in artificial intelligence, video surveillance, identity authentication, human-machine interaction and so on. However, skin color detection has high false positive rate in complex background and AdaBoost algorithm was not satisfactory for detection of multi-pose and multi-face image. So a novel face detection method combined with skin color detection and an improved AdaBoost algorithm is proposed in this paper. First, it applies skin model segmentation and morphological operators to detect skin regions in the image. And according to the geometrical characteristics of the face, it screens the candidate face regions. Then by the improved classifiers in a cascade structure based on AdaBoost, it achieves more accurate promising regions of face. The experiment results show that this face detection algorithm improves the detection speed in both the quality of detection, and it can effectively reduce the error detection rate of single test method. This method has a good performance on image with complex background. Above all, this method has a certain theory value and practical value. ©2010 ieee.

关键词： Face recognition

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A combined physical and statistical approach to colour constancy

A combined physical and statistical approach to colour const...

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conference on computer vision and pattern recognition (cvpr)

作者： G. Schaefer S. Hordley G. Finlayson School of Computing and Informatics Nottingham Trent University UK School of Computing Sciences University of East Anglia UK

Computational colour constancy tries to recover the colour of the scene illuminant of an image. Colour constancy algorithms can, in general, be divided into two groups: statistics-based approaches that exploit statistical knowledge of common lights and surfaces, and physics-based algorithms which are based on an understanding of how physical processes such as highlights manifest themselves in images. A combined physical and statistical colour constancy algorithm that integrates the advantages of the statistics-based colour by correlation method with those of a physics-based technique based on the dichromatic reflectance model is introduced. In contrast to other approaches not only a single illuminant estimate is provided but a set of likelihoods for a given illumination set. Experimental results on the benchmark Simon Fraser image database show the combined method to clearly outperform purely statistical and purely physical algorithms.

关键词： Neural networks Layout Reflectivity Lighting Image databases computer vision Informatics Color Correlation Digital cameras

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A minimal solution for relative pose with unknown focal length

A minimal solution for relative pose with unknown focal leng...

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conference on computer vision and pattern recognition (cvpr)

作者： H. Stewenius D. Nister F. Kahl F. Schaffalitzky Lund University Sweden University of Kentucky Lexington USA University of California San Diego USA University of Oxford UK

Assume that we have two perspective images with known intrinsic parameters except for an unknown common focal length. It is a minimally constrained problem to find the relative orientation between the two images given six corresponding points. We present an efficient solution to the problem and show that there are 15 solutions in general (including complex solutions). To the best of our knowledge this was a previously unsolved problem. The solutions are found through eigen-decomposition of a 15/spl times/15 matrix. The matrix itself is generated in closed form. We demonstrate through practical experiments that the algorithm is correct and numerically stable.

关键词： Cameras computer vision Equations Image reconstruction Video sequences Engines Stability analysis Noise measurement Computational geometry

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