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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"

共 6858 条记录，以下是4801-4810 订阅

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Finding junctions using the image gradient

Finding junctions using the image gradient

引用

conference on computer vision and pattern recognition (cvpr)

作者： D.J. Beymer MIT Artificial Intelligence Laboratory Cambridge MA USA

The author proposes a junction detector that works by filling in gaps at junctions in edge maps. It uses the image gradient to guide extensions of disconnected edges at junctions. A novel representation for the gradient, the bow tie map, is used to implement the endpoint growing rules, which include following gradient ridges and using saddle points in the gradient magnitude. The authors demonstrate the junction detector on real imagery.< >

关键词： Image edge detection Imaging phantoms Detectors computer vision Smoothing methods Optical filters Optical noise Artificial intelligence Laboratories Machine vision

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Closed-form solutions for physically-based shape modeling and recognition

Closed-form solutions for physically-based shape modeling an...

引用

conference on computer vision and pattern recognition (cvpr)

作者： S. Sclaroff A. Pentland Vision and Modeling Group The Media Lab Massachusetts Institute of Technology USA

An efficient, physically based solution for recovering a 3-D solid model from collections of 3-D surface measurements is presented. Given a sufficient number of independent measurements, the solution is overconstrained and unique except for rotational symmetries. A physically based object recognition method that allows simple, closed-form comparisons of recovered 3-D solid models is given. The performance of these methods is evaluated using both synthetic and real laser rangefinder data.< >

关键词： Shape Solid modeling Equations Deformable models Databases Object recognition Surface fitting Finite element methods Predictive models Face recognition

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Feature correspondence by interleaving shape and texture computations

Feature correspondence by interleaving shape and texture com...

引用

conference on computer vision and pattern recognition (cvpr)

作者： D. Beymer Artificial Intelligence Laboratory and Center for Biological and Computational Learning Massachusetts Institute of Technology Cambridge MA USA

The correspondence problem in computer vision is basically a matching task between two or more sets of features. We introduce a vectorized image representation, which is a feature-based representation where correspondence has been established with respect to a reference image. The representation consists of two image measurements made at the feature points: shape and texture. Feature geometry, or shape, is represented using the (x,y) locations of features relative to the some standard reference shape. Image grey levels, or texture, are represented by mapping image grey levels onto the standard reference shape. Computing this representation is essentially a correspondence task and in this paper we explore on automatic technique for "vectorizing" face images. Our face vectorizer alternates back and forth between computation steps for shape and texture, and a key idea is to structure the two computations so that each one uses the output of the other. In addition to describing the vectorizer, an application to the problem of facial feature detection is presented.

关键词： Interleaved codes Biology computing Image texture analysis Artificial intelligence Learning Shape measurement Geometry Face detection Face recognition Image analysis

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Projective registration with difference decomposition

Projective registration with difference decomposition

引用

conference on computer vision and pattern recognition (cvpr)

作者： M. Gleicher Apple Research Laboratorie Infinite Loop Cupertino CA USA

Current methods for registering image regions perform well for simple transformations or large image regions. The author presents a new method that is better able to handle small image regions as they deform with nonlinear transformations. He introduces difference decomposition, a novel approach to solving the registration problem. The method is a generalization of previous methods and can better handle nonlinear transforms. Although the methods are general, he focuses on projective transformations and introduces piecewise-projective transformations for modeling the motions of non-planar objects. He concludes with examples from a prototype implementation.

关键词： computer vision Application software Target tracking computer errors Laboratories Prototypes Image recognition Surveillance computer graphics Image coding

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Generic recognition through qualitative reasoning about 3-D shape and object function

Generic recognition through qualitative reasoning about 3-D ...

引用

conference on computer vision and pattern recognition (cvpr)

作者： L. Stark K. Bowyer Department of Computer Science and Engineering University of South Florida Tampa FL USA

The work which demonstrates the feasibility of a different approach to 3-D object recognition is described. The authors construct a definition of a generic object category, such as a chair, in terms of the function required of the object. This definition is based on qualitative reasoning about 3-D shape, and does not imply any particular geometric or structural model for an object. Thus, this approach has the potential to lead to recognition systems of much greater generality than current CAD-based or model-based approaches.< >

关键词： Shape Solid modeling Object recognition Geometry computer science Knowledge engineering computer vision

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Automated mosaicing with super-resolution zoom

Automated mosaicing with super-resolution zoom

引用

conference on computer vision and pattern recognition (cvpr)

作者： D. Capel A. Zisserman Robotics Research Group Department of Engineering Science University of Oxford Oxford UK

We describe mosaicing for a sequence of images acquired by a camera rotating about its centre. The novel contributions are in two areas. First, in the automation and estimation of image registration: images

关键词： Maximum likelihood estimation Spatial resolution Cameras Degradation Image resolution Quantization Robotics and automation Identity-based encryption Robot vision systems Image registration

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The gas-leaking sensing system and the vision navigation and orientation of mobile manipulator

The gas-leaking sensing system and the vision navigation and...

引用

2006 ieee International conference on Robotics and Biomimetics, ROBIO 2006

作者： Cheng-jun, Ding Ping, Duan Bing-qing, Liu Ming-lu, Zhang School of Mechanical Engineering Hebei University of Technology Tianjin 300130 China

ISBN: (纸本)1424405718

In this paper, we mainly research three aspects content, that is 1) The intelligent sensing system for chemical gas leak, which consists of three units. Many sensors are installed on the twelve different areas of easily leaking, if there are leak, will transmit the leaking area to the main computer of manipulator. 2) According to the 1)' information, a navigation system of mobile manipulator is designed, which puts forward using CCD to recognize colour road, which is laid on the ground, to arrive at the aim. In the process of navigation, adopts a new fuzzy control strategy, when the curving extent of path satisfies definite condition, adopting fuzzy control with Genetic Algorithm off-line optimizing the membership function parameters of fuzzy controller. 3) After arriving at the leaking area, the exact orientation of manipulator is implemented by visual and ultrasonic sensor. Segmenting the objective figure uses group colour up method and recognition object uses invariant moments. The whole process is applied on the HEBUT-II intelligent mobile manipulator. The result proves its validity and feasibility. ©2006 ieee.

关键词： Manipulators

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Geometric blur for template matching

Geometric blur for template matching

引用

conference on computer vision and pattern recognition (cvpr)

作者： A.C. Berg J. Malik Computer Science Division University of California Berkeley USA

ISBN: (纸本)0769512720

We address the problem of finding point correspondences in images by way of an approach to template matching that is robust under affine distortions. This is achieved by applying "geometric blur" to both the template and the image, resulting in a fall-off in similarity that is close to linear in the norm of the distortion between the template and the image. Results in wide baseline stereo correspondence, face detection, and feature correspondence are included.

关键词： Image edge detection Stereo vision computer vision Object recognition Uncertainty Lighting computer science Robustness Face detection Concrete

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Learning feature distance measures for image correspondences

Learning feature distance measures for image correspondences

引用

conference on computer vision and pattern recognition (cvpr)

作者： X. Chen T.-J. Cham School of Computer Engineering Nanyang Technological University Singapore

ISBN: (纸本)0769523722

Standard but ad hoc measures such as sum-of-squared pixel differences (SSD) are often used when comparing and registering two images that have not been previously observed before. In this paper, we propose a framework to address the problem of learning a parametric feature distance measure to measure the dissimilarity between pairs of images. The method is based on optimizing the parameters of the distance measure in order to minimize correspondence classification errors on training data. Because the learning process involves relative (rather than absolute) visual content between image pairs, the learned distance measure may also be applied to other images with very different visual content. Results on matching classification with a wide variety of image content show that the learned feature distance measure clearly outperforms the standard measures of SSD, chamfer and Bhattacharyya histogram distances.

关键词： Training data Measurement standards Pixel Optimization methods Histograms Image matching Object detection Image retrieval Content based retrieval Testing

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Optimal nonlinear pattern restoration from noisy binary figures

Optimal nonlinear pattern restoration from noisy binary figu...

引用

conference on computer vision and pattern recognition (cvpr)

作者： D. Schonfeld Signal and Image Research Laboratory Department of Electrical Engineering and Computer Science University of Illinois Chicago Chicago IL USA

A mathematical framework for the solution of statistical inference problems on a class of random sets is proposed. It is based on a new definition of expected pattern. The least-mean-difference estimator (restoration filter) is proved, under certain conditions, to be equivalent to the minimization of the measure of size (area) of the set-difference between the original pattern and the expected pattern of the estimated (restored) pattern. Consequently, it is proved that, under certain conditions, if the estimator (restoration filter) is unbiased, then it is the least mean difference estimator (restoration filter).< >

关键词： Noise figure Image restoration pattern analysis Filters Set theory Signal restoration Laboratories Area measurement Size measurement Morphology

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