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检索条件"任意字段=26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR"

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What Can Missing Correspondences Tell Us About 3D Structure and Motion?

What Can Missing Correspondences Tell Us About 3D Structure ...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.9

作者： Christopher Zach Arnold Irschara Horst Bischof VRVis Research Center University of North Carolina Chapel Hill USA Institute of Computer Graphics and Vision Graz Austria

Practically all existing approaches to structure and motion computation use only positive image correspondences to verify the camera pose hypotheses. Incorrect epipolar geometries are solely detected by identifying outliers among the found correspondences. Ambigous patterns in the images are often incorrectly handled by these standard methods. In this work we propose two approaches to overcome such problems. First, we apply non-monotone reasoning on view triplets using a Bayesian formulation. In contrast to two-view epipolar geometry, image triplets allow the prediction of features in the third image. Absence of these features (i.e. missing correspondences) enables additional inference about the view triplet. Furthermore, we integrate these view triplet handling into an incremental procedure for structure and motion computation. thus, our approach is able to refine the maintained 3D structure when additional image data is provided.

关键词： Image reconstruction Layout Geometry Solid modeling computer vision Cameras Engines Pipelines computer graphics Bayesian methods

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Enhancing Photographs with Near Infrared Images

Enhancing Photographs with Near Infrared Images

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.12

作者： Xiaopeng Zhang Terence Sim Xiaoping Miao School of Computing National University of Singapore Singapore

Near Infra-Red (NIR) images of natural scenes usually have better contrast and contain rich texture details that may not be perceived in visible light photographs (VIS). In this paper, we propose a novel method to enhance a photograph by using the contrast and texture information of its corresponding NIR image. More precisely, we first decompose the NIR/VIS pair into average and detail wavelet subbands. We then transfer the contrast in the average sub-band and transfer texture in the detail subbands. We built a special camera mount that optically aligns two consumer-grade digital cameras, one of which was modified to capture NIR. Our results exhibit higher visual quality than tone-mapped HDR images, showing that NIR imaging is useful for computational photography.

关键词： Infrared imaging Digital cameras Dynamic range Layout Filters Optical computing Optical imaging Photography computer displays Image converters

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A Two-Frame theory of Motion, Lighting and Shape

A Two-Frame Theory of Motion, Lighting and Shape

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.10

作者： Ronen Basri Darya Frolova Department of Computer Science and Applied Math Weizmann Institute of Science Rehovot Israel

this paper explores how shape, motion, and lighting interact in the case of a two-frame motion sequence. We consider a rigid object with Lambertian reflectance properties undergoing small motion with respect to both a camera and a stationary point light source. Assuming orthographic projection, we derive a single, first order quasilinear partial differential equation that relates shape, motion, and lighting, while eliminating out the albedo. We show how this equation can be solved, when the motion and lighting parameters are known, to produce a 3D reconstruction of the object. A solution is obtained using the method of characteristics and can be refined by adding regularization. We further show that both smooth bounding contours as well as surface markings can be used to derive Dirichlet boundary conditions. Experimental results demonstrate the quality of this reconstruction.

关键词： Shape Image reconstruction Brightness Cameras Boundary conditions Reflectivity Light sources Partial differential equations Surface reconstruction Photometry

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Calibration and Rectification for Reflection Stereo

Calibration and Rectification for Reflection Stereo

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.9

作者： Masao Shimizu Masatoshi Okutomi Tokyo Institute of Technology Japan

this paper presents a calibration and rectification method for single-camera range estimation using a single complex image with a transparent plate or a double-sided half-mirror plate, which are collectively called a reflection stereo. the range to an object is obtainable by finding the correspondence on a constraint line in the complex image, which consists of a surface and a rear-surface reflected image in the transparent plate, or also includes a transmitted and internal reflected image through a double-sided half-mirror plate. the range estimation requires extrinsic parameters of the reflection stereo that include the shape and position of the plate and its refraction index. the proposed method assumes that the plate is non-parallel but planar for a local region around the point of interest in the complex image. the method estimates the extrinsic parameters from a set of displacements in the complex images. Experiments using real images demonstrate the effectiveness of the proposed calibration and rectification method along with fine range estimation results.

关键词： Calibration Optical reflection Parameter estimation Cameras Shape Optical refraction Image generation Stereo vision Object detection Optical detectors

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Visual Synset: Towards a Higher-level Visual Representation

Visual Synset: Towards a Higher-level Visual Representation

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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.7

作者： Yan-Tao Zheng Ming Zhao Shi-Yong Neo Tat-Seng Chua Qi Tian National University of Singapore Singapore Google Inc. USA Institute for Infocomm Research Singapore

We present a higher-level visual representation, visual synset, for object categorization. the visual synset improves the traditional bag of words representation with better discrimination and invariance power. First, the approach strengthens the inter-class discrimination power by constructing an intermediate visual descriptor, delta visual phrase, from frequently co-occurring visual word-set with similar spatial context. Second, the approach achieves better intra-class invariance power, by clustering delta visual phrases into visual synset, based their probabilistic 'semantics', i.e. class probability distribution. Hence, the resulting visual synset can partially bridge the visual differences of images of same class. the tests on Caltech-101 and Pascal-VOC 05 dataset demonstrated that the proposed image representation can achieve good accuracies.

关键词： Probability distribution Object recognition Bridges Vector quantization Robustness Motorcycles Bicycles Testing Image representation Solid modeling

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A Parallel Decomposition Solver for SVM: Distributed Dual Ascend using Fenchel Duality

A Parallel Decomposition Solver for SVM: Distributed Dual As...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.1

作者： Tamir Hazan Amit Man Amnon Shashua School of Engineering & Computer Science Hebrew University of Jerusalem Israel

We introduce a distributed algorithm for solving large scale Support Vector Machines (SVM) problems. the algorithm divides the training set into a number of processing nodes each running independently an SVM sub-problem associated with its subset of training data. the algorithm is a parallel (Jacobi) block-update scheme derived from the convex conjugate (Fenchel Duality) form of the original SVM problem. Each update step consists of a modified SVM solver running in parallel over the sub-problems followed by a simple global update. We derive bounds on the number of updates showing that the number of iterations (independent SVM applications on sub-problems) required to obtain a solution of accuracy ε is O(log(1/ε)). We demonstrate the efficiency and applicability of our algorithms by running on large scale experiments on standardized datasets while comparing the results to the state-of-the-art SVM solvers.

关键词： Support vector machines Convergence Large-scale systems Kernel Concurrent computing Support vector machine classification Matrix decomposition Distributed algorithms Distributed computing Workstations

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A Deformable Local Image Descriptor

A Deformable Local Image Descriptor

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.1

作者： Hong Cheng Zicheng Liu Nanning Zheng Jie Yang Carnegie Mellon University Pittsburgh USA Xi''an Jiaotong University Xi'an China Microsoft Research Limited Redmond USA

this paper presents a novel local image descriptor that is robust to general image deformations. A limitation with traditional image descriptors is that they use a single support region for each interest point. For general image deformations, the amount of deformation for each location varies and is unpredictable such that it is difficult to choose the best scale of the support region. To overcome this difficulty, we propose to use multiple support regions of different sizes surrounding an interest point. A feature vector is computed for each support region, and the concatenation of these feature vectors forms the descriptor for this interest point. Furthermore, we propose a new similarity measure model, Local-to-Global Similarity (LGS) model, for point matching that takes advantage of the multi-size support regions. Each support region acts as a 'weak' classifier and the weights of these classifiers are learned in an unsupervised manner. the proposed approach is evaluated on a number of images with real and synthetic deformations. the experiment results show that our method outperforms existing techniques under different deformations.

关键词： Lenses Image matching computer vision Object recognition Histograms Shape Matched filters Robustness Object detection Image recognition

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Local Minima Free Parameterized Appearance Models

Local Minima Free Parameterized Appearance Models

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.5

作者： Minh Hoai Nguyen Fernando De la Torre Robotics Institute Carnegie Mellon University Pittsburgh PA USA

Parameterized Appearance Models (PAMs) (e.g. Eigen-tracking, Active Appearance Models, Morphable Models) are commonly used to model the appearance and shape variation of objects in images. While PAMs have numerous advantages relative to alternate approaches, they have at least two drawbacks. First, they are especially prone to local minima in the fitting process. Second, often few if any of the local minima of the cost function correspond to acceptable solutions. To solve these problems, this paper proposes a method to learn a cost function by explicitly optimizing that the local minima occur at and only at the places corresponding to the correct fitting parameters. To the best of our knowledge, this is the first paper to address the problem of learning a cost function to explicitly model local properties of the error surface to fit PAMs. Synthetic and real examples show improvement in alignment performance in comparison with traditional approaches.

关键词： Cost function Principal component analysis Surface fitting Training data Active shape model Optimization methods Testing Robots Active appearance model computer errors

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Shape Prior Segmentation of Multiple Objects with Graph Cuts

Shape Prior Segmentation of Multiple Objects with Graph Cuts

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.3

作者： Nhat Vu B. S. Manjunath Department of Electrical and Computer Engineering University of California Santa Barbara CA USA

We present a new shape prior segmentation method using graph cuts capable of segmenting multiple objects. the shape prior energy is based on a shape distance popular with level set approaches. We also present a multiphase graph cut framework to simultaneously segment multiple, possibly overlapping objects. the multiphase formulation differs from multiway cuts in that the former can account for object overlaps by allowing a pixel to have multiple labels. We then extend the shape prior energy to encompass multiple shape priors. Unlike variational methods, a major advantage of our approach is that the segmentation energy is minimized directly without having to compute its gradient, which can be a cumbersome task and often relies on approximations. Experiments demonstrate that our algorithm can cope with image noise and clutter, as well as partial occlusions and affine transformations of the shape.

关键词： Image segmentation Level set Shape measurement Multi-stage noise shaping Pixel Runtime Kernel Labeling Probability Background noise

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Dense 3D Motion Capture from Synchronized Video Streams

Dense 3D Motion Capture from Synchronized Video Streams

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26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.4

作者： Yasutaka Furukawa Jean Ponce Department of Computer Science and Beckman Institute University of Illinois Urbana USA LIENS (CNRS/ENS/INRIA UMR 8548) Willow Paris France

this paper proposes a novel approach to nonrigid, markerless motion capture from synchronized video streams acquired by calibrated cameras. the instantaneous geometry of the observed scene is represented by a polyhedral mesh with fixed topology. the initial mesh is constructed in the first frame using the publicly available PMVS software for multi-view stereo [7]. Its deformation is captured by tracking its vertices over time, using two optimization processes at each frame: a local one using a rigid motion model in the neighborhood of each vertex, and a global one using a regularized nonrigid model for the whole mesh. Qualitative and quantitative experiments using seven real datasets show that our algorithm effectively handles complex nonrigid motions and severe occlusions.

关键词： Streaming media Layout Motion estimation Cameras Tracking Shape Image motion analysis Deformable models Surface reconstruction Image reconstruction

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