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检索条件"任意字段=2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006"

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Parameter estimation for MRF stereo

Parameter estimation for MRF stereo

引用

conference on computer vision and pattern recognition (cvpr)

作者： L. Zhang S.M. Seitz University of Washington USA

This paper presents a novel approach for estimating parameters for MRF-based stereo algorithms. This approach is based on a new formulation of stereo as a maximum a posterior (MAP) problem, in which both a disparity map and MRF parameters are estimated from the stereo pair itself. We present an iterative algorithm for the MAP estimation that alternates between estimating the parameters while fixing the disparity map and estimating the disparity map while fixing the parameters. The estimated parameters include robust truncation thresholds, for both data and neighborhood terms, as well as a regularization weight. The regularization weight can be either a constant for the whole image, or spatially-varying, depending on local intensity gradients. In the latter case, the weights for intensity gradients are also estimated. Experiments indicate that our approach, as a wrapper for existing stereo algorithms, moves a baseline belief propagation stereo algorithm up six slots in the middlebury rankings.

关键词： Parameter estimation Stereo vision Pixel Belief propagation Iterative algorithms Robustness computer vision Markov random fields Joining processes Energy measurement

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Sign Classification using Local and Meta-Features

Sign Classification using Local and Meta-Features

引用

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

作者： M.A. Mattar A.R. Hanson E.G. Learned-Miller Computer Vision Laboratory Department of Computer Science University of Massachusetts Amherst MA USA

Our world is populated with visual information that a sighted person makes use of daily. Unfortunately, the visually impaired are deprived from such information, which limits their mobility in unconstrained environments. To help alleviate this we are developing a wearable system [1, 19] that is capable of detecting and recognizing signs in natural scenes. The system is composed of two main components, sign detection and recognition. The sign detector, uses a conditional maximum entropy model to find regions in an image that correspond to a sign. The sign recognizer matches the hypothesized sign regions with sign images in a database. The system decides if the most likely sign is correct or if the hypothesized sign region does not belong to a sign in the database. Our data sets encompass a wide range of variability including changes in lighting, orientation and viewing angle. In this paper, we present an overview of the system while while paying particular attention to the recognition component. Tested on 3,975 sign images from two different data sets, the recognition phase achieves accuracies of 99.5% with 35 distinct signs and 92.8% with 65 distinct signs.

关键词： Image recognition Image databases Detectors computer vision Cameras Shape pattern recognition Laboratories computer science Layout

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Detecting, localizing and recovering kinematics of textured animals

Detecting, localizing and recovering kinematics of textured ...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Deva Ramanan D.A. Forsyth K. Barnard University of California Berkeley Berkeley CA USA University of Arizona Tucson Tucson AZ USA

We develop and demonstrate an object recognition system capable of accurately detecting, localizing, and recovering the kinematic configuration of textured animals in real images. We build a deformation model of shape automatically from videos of animals and an appearance model of texture from a labeled collection of animal images, and combine the two models automatically. We develop a simple texture descriptor that outperforms the state of the art. We test our animal models on two datasets; images taken by professional photographers from the Corel collection, and assorted images from the Web returned by Google. We demonstrate quite good performance on both datasets. Comparing our results with simple baselines, we show that for the Google set, we can recognize objects from a collection demonstrably hard for object recognition.

关键词： Kinematics Animals Videos Object detection Shape Deformable models Object recognition Testing Head Leg

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Wavelet-based Processing of EEG Data for Brain-computer Interfaces

Wavelet-based Processing of EEG Data for Brain-Computer Inte...

引用

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

作者： Dong Seon Cheng V. D'Amato V. Murino Dipartimento di Informatica Università di Verona Italy Università di Verona Italy

Brain-computer Interfaces based on non-invasive electroencephalographic (EEG) signals were recently made practical through sophisticated algorithms and clever systems, in such a way that the dream of effortlessly translating volition into action is coming true, albeit in a limited way. However, a low signal-to-noise ratio and the presence of frequent artefacts, such as eye blinks, contaminate the recordings and make the recognition of the underlying mental processes difficult. In this study, a novel waveletbased signal processing technique, ContinuousWavelet Regression, has been applied to refine EEG data in a wellknown setting. The recordings of spontaneous (i.e., asynchronous) signals of subjects performing highly different cognitive tasks have been processed by our algorithm, and then analyzed and classified, obtaining very promising results as compared with those obtained by previous studies.

关键词： Electroencephalography Brain computer interfaces Continuous wavelet transforms Signal processing Discrete wavelet transforms Signal processing algorithms Frequency Wavelet transforms Signal to noise ratio pattern recognition

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A factorization-based approach to articulated motion recovery

A factorization-based approach to articulated motion recover...

引用

conference on computer vision and pattern recognition (cvpr)

作者： J. Yan M. Pollefeys Department of Computer Science University of North Carolina Chapel Hill Chapel Hill NC USA

This paper addresses the subspace properties and the recovery of articulated motion. We point out that the global motion subspace of an articulated object is a combination of a number of intersecting rigid motion subspaces of the parts. Depending on whether a link of two parts is a joint or an axis, the global motion subspace loses one or two in rank for each link. The rank loss results from the intersection between the rigid motion subspaces of linked parts. Furthermore, the intersection is, in fact, the motion subspace of the link. From these observations, we describe the rank constraint of the global motion subspace of an articulated object; we give an algorithm to recover the image motion of a link, either a joint or an axis; and we propose a novel but simple approach, which is based on subspace clustering, to recover articulated shape and motion from a single-view image sequence.

关键词： Shape Layout Cameras computer science Subspace constraints Clustering algorithms Image sequences Motion estimation Computational geometry Robot vision systems

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Indexing with unknown illumination and pose

Indexing with unknown illumination and pose

引用

conference on computer vision and pattern recognition (cvpr)

作者： I. Kemelmacher R. Basri Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel

The task of identifying 3D objects in 2D images is difficult due to variation in objects' appearance with changes in pose and lighting. The task is further complicated by the presence of occlusion and clutter. Shape indexing is a method for rapid association between features identified in an image and their corresponding 3D features stored in a database. Previous indexing methods ignored variations due to lighting, restricting the approach to polyhedral objects. In this paper, we further develop these methods to handle variations in both pose and lighting. We focus on rigid objects undergoing a scaled-orthographic projection and use spherical harmonics to represent lighting. The resulting integrated algorithm can recognize 3D objects from a single input image; furthermore, it recovers the pose and lighting of each familiar object in the given image. The algorithm has been tested on a database of real objects, demonstrating its performance on cluttered scenes under a variety of poses and illumination conditions.

关键词： Indexing Lighting Shape Spatial databases Image databases Image recognition Layout pattern recognition computer science Testing

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Vehicle segmentation and tracking from a low-angle off-axis camera

Vehicle segmentation and tracking from a low-angle off-axis ...

引用

conference on computer vision and pattern recognition (cvpr)

作者： N.K. Kanhere S.J. Pundlik S.T. Birchfield Electrical and Computer Engineering Department Clemson University Clemson SC USA

We present a novel method for visually monitoring a highway when the camera is relatively low to the ground and on the side of the road. In such a case, occlusion and the perspective effects due to the heights of the vehicles cannot be ignored. Features are detected and tracked throughout the image sequence, and then grouped together using a multilevel homography, which is an extension of the standard homography to the low-angle situation. We derive a concept called the relative height constraint that makes it possible to estimate the 3D height of feature points on the vehicles from a single camera, a key part of the technique. Experimental results on several different highways demonstrate the system's ability to successfully segment and track vehicles at low angles, even in the presence of severe occlusion and significant perspective changes.

关键词： Cameras Road vehicles Traffic control computerized monitoring Road transportation Image sequences Automotive engineering US Department of Transportation computer vision Automated highways

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Articulated structure from motion by factorization

Articulated structure from motion by factorization

引用

conference on computer vision and pattern recognition (cvpr)

作者： P. Tresadern I. Reid Department of Engineering Science University of Oxford Oxford UK

Multibody affine structure from motion (SFM) methods commonly assume independent motion between objects such that the 'measurement matrix' has rank 4k. When multiple views are available, each object is then independently calibrated to a metric co-ordinate frame. However, articulated motion results in a further decrease in rank - a fact that we exploit to detect articulated objects and determine their degrees of freedom using simple linear methods. Furthermore, these objects cannot be recovered and calibrated independently since this violates articulation constraints. We show that articulation constraints can be imposed during factorization and self-calibration to recover consistent 3D structure and motion, from which link lengths and joint angles can be computed. The stability of the method is evaluated using synthetic data for comparison with ground truth and results are also presented for real image sequences.

关键词： Cameras Tracking Object detection Motion detection Layout Motion segmentation computer vision Shape Humans Stability

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Architecture and Performance of the HI-Space Projector-Camera Interface

Architecture and Performance of the HI-Space Projector-Camer...

引用

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

作者： R. May B. Baddeley Pacific Northwest National Laboratory USA

This paper presents the architecture and configuration of the Human Information Workspace (HI-Space) interaction environment. HI-Space is a projector-camera-microphone system that recognizes gesture, object and speech input. The system creates input stream events and uses HI-Space aware interface components allowing the creation of independent applications through an API. To help understand performance characteristics of HI-Space, a procedure is presented that was used to determine the total system lag of the HI-Space to be 71 ms with an 11 ms standard deviation. A study is also presented that directly compares HI-Space and a mouse in the task of acquiring stationary targets. The study shows that users can acquire targets faster and just as accurately on the HI-Space system. Finally, an example application to support analysis of 3D biological data sets is discussed. The application is an ongoing research effort to explore complex interface design using the HI-Space architecture.

关键词： Cameras computer vision Application software computer displays Libraries Fingers computer architecture Humans Speech recognition Mice

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The distinctiveness, detectability, and robustness of local image features

The distinctiveness, detectability, and robustness of local ...

引用

conference on computer vision and pattern recognition (cvpr)

作者： G. Carneiro A.D. Jepson Department of Computer Science University of British Columbia Vancouver BC Canada Department of Computer Science University of Toronto Toronto ONT Canada

We introduce a new method that characterizes typical local image features (e.g., SIFT, phase feature) in terms of their distinctiveness, detectability, and robustness to image deformations. This is useful for the task of classifying local image features in terms of those three properties. The importance of this classification process for a recognition system using local features is as follows: a) reduce the recognition time due to a smaller number of features present in the test image and in the database of model features; b) improve the recognition accuracy since only the most useful features for the recognition task are kept in the model database; and c) increase the scalability of the recognition system given the smaller number of features per model. A discriminant classifier is trained to select well behaved feature points. A regression network is then trained to provide quantitative models of the detection distributions for each selected feature point. It is important to note that both the classifier and the regression network use image data alone as their input. Experimental results show that the use of these trained networks not only improves the performance of our recognition system, but it also significantly reduces the computation time for the recognition process.

关键词： Robustness Image recognition System testing Scalability computer science Image databases Spatial databases Character recognition Phase detection computer networks

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