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检索条件"任意字段=26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013"

共 656 条记录，以下是471-480 订阅

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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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Learning 4D Action Feature Models for Arbitrary View Action recognition

Learning 4D Action Feature Models for Arbitrary View Action ...

引用

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

作者： Pingkun Yan Saad M. Khan Mubarak Shah Computer Vision Laboratory University of Central Florida Orlando FL USA

In this paper we present a novel approach using a 4D (x,y,z,t) action feature model (4D-AFM) for recognizing actions from arbitrary views. the 4D-AFM elegantly encodes shape and motion of actors observed from multiple views. the modeling process starts with reconstructing 3D visual hulls of actors at each time instant. Spatiotemporal action features are then computed in each view by analyzing the differential geometric properties of spatio-temporal volumes (3D STVs) generated by concatenating the actor's silhouette over the course of the action (x,y,t). these features are mapped to the sequence of 3D visual hulls over time (4D) to build the initial 4D-AFM. Actions are recognized based on the scores of matching action features from the input videos to the model points of 4D-AFMs by exploiting pairwise interactions of features. Promising recognition results have been demonstrated on the multi-view IXMAS dataset using both single and multi-view input videos.

关键词： Shape Videos Object recognition Humans computer vision Image reconstruction Spatiotemporal phenomena Costs Cameras Graphical models

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Image Decomposition into Structure and Texture Subcomponents with Multifrequency Modulation Constraints

Image Decomposition into Structure and Texture Subcomponents...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.8

作者： Georgios Evangelopoulos Petros Maragos School of Electrical and Computer Engineering National and Technical University of Athens Greece

Texture information in images is coupled with geometric macrostructures and piecewise-smooth intensity variations. Decomposing an image f into a geometric structure component u and a texture component v is an inverse estimation problem, essential for understanding and analyzing images depending on their content. In this paper, we present a novel combined approach for simultaneous texture from structure separation and multiband texture modeling. First, we formulate a new, variational decomposition scheme, involving an explicit texture reconstruction constraint (prior) formed by the responses of selected frequency-tuned linear filters. this forms a 'u + Kv' image model of K + 1 components. Subsequent texture modeling is applied to the estimated v component and its consistency is compared to using the complete, initial image f. the decomposition step, functioning as an advanced texture-front end, improves clustering and classification performance, for various multiband features. the proposed method can be generalized to other texture models or applications.

关键词： Image decomposition Image texture analysis Frequency Shape Image analysis Image reconstruction Nonlinear filters Solid modeling Image edge detection Image segmentation

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Real-Time Face Pose Estimation from Single Range Images

Real-Time Face Pose Estimation from Single Range Images

引用

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

作者： Michael D. Breitenstein Daniel Kuettel thibaut Weise Luc van Gool Hanspeter Pfister Computer Vision Laboratory ETH Zurich Switzerland School of Engineering and Applied Sciences Harvard University Cambridge MA USA

We present a real-time algorithm to estimate the 3D pose of a previously unseen face from a single range image. Based on a novel shape signature to identify noses in range images, we generate candidates for their positions, and then generate and evaluate many pose hypotheses in parallel using modern graphics processing units (GPUs). We developed a novel error function that compares the input range image to precomputed pose images of an average face model. the algorithm is robust to large pose variations of ±90° yaw, ±45° pitch and ±30° roll rotation, facial expression, partial occlusion, and works for multiple faces in the field of view. It correctly estimates 97.8% of the poses within yaw and pitch error of 15° at 55.8 fps. To evaluate the algorithm, we built a database of range images with large pose variations and developed a method for automatic ground truth annotation.

关键词： Face detection Robustness Nose Graphics Runtime computer vision Laboratories Shape Image generation Error correction

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On Controlling Light Transport in Poor Visibility Environments

On Controlling Light Transport in Poor Visibility Environmen...

引用

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

作者： Mohit Gupta Srinivasa G. Narasimhan Yoav Y. Schechner School of Computer Sc. Carnegie Mellon University Pittsburgh USA Department of Electrical Engineering Technion-Israel Institute of Technology Haifa Israel

Poor visibility conditions due to murky water, bad weather, dust and smoke severely impede the performance of vision systems. Passive methods have been used to restore scene contrast under moderate visibility by digital post-processing. However, these methods are ineffective when the quality of acquired images is poor to begin with. In this work, we design active lighting and sensing systems for controlling light transport before image formation, and hence obtain higher quality data. First, we present a technique of polarized light striping based on combining polarization imaging and structured light striping. We show that this technique out-performs different existing illumination and sensing methodologies. Second, we present a numerical approach for computing the optimal relative sensor-source position, which results in the best quality image. Our analysis accounts for the limits imposed by sensor noise.

关键词： Lighting control Layout Backscatter Optical polarization Control systems Cameras computer vision Image restoration Image quality Light scattering

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Discriminative Modeling by Boosting on Multilevel Aggregates

Discriminative Modeling by Boosting on Multilevel Aggregates

引用

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

作者： Jason J. Corso Computer Science and Engineering Suny at Buffalo Buffalo USA

this paper presents a new approach to discriminative modeling for classification and labeling. Our method, called Boosting on Multilevel Aggregates (BMA), adds a new class of hierarchical, adaptive features into boosting-based discriminative models. Each pixel is linked with a set of aggregate regions in a multilevel coarsening of the image. the coarsening is adaptive, rapid and stable. the multilevel aggregates present additional information rich features on which to boost, such as shape properties, neighborhood context, hierarchical characteristics, and photometric statistics. We implement and test our approach on three two-class problems: classifying documents in office scenes, buildings and horses in natural images. In all three cases, the majority, about 75%, of features selected during boosting are our proposed BMA features rather than patch-based features. this large percentage demonstrates the discriminative power of the multilevel aggregate features over conventional patch-based features. Our quantitative performance measures show the proposed approach gives superior results to the state-of-the-art in all three applications.

关键词： Boosting Aggregates Labeling Pixel Shape Photometry Statistics Testing Layout Horses

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Cell Motion Analysis Without Explicit Tracking

Cell Motion Analysis Without Explicit Tracking

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.2

作者： Richard Souvenir Jerrod Kraftchick Sangho Lee Mark G. Clemens Min C. Shin Department of Computer Science North Carolina State University Charlotte USA Department of Biology North Carolina State University Charlotte USA

Automated cell tracking using in vivo imagery is difficult, in general, due to the noise inherent in the imaging process, occlusions, varied cell appearance over time, motion of other tissue (distractors), and cells traveling in and out of the image plane. For certain types of cells these problems are exacerbated due to erratic motion patterns. In this paper, we introduce the Radial Flow Transform, which provides motion estimates for objects of interest in a scene without explicitly tracking each object. the transform is robust to misdetected objects, temporally-disjoint motion events, and can represent multiple directions of flow at a single location. We provide operations to convert to and from a vector field representation. this allows for intuitive reasoning about the motion patterns in a scene. We demonstrate results on synthetic data and in vivo microscopy video of a mouse liver.

关键词： Motion analysis Tracking Cells (biology) In vivo Motion estimation Layout Microscopy Biomedical imaging Roads Mice

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Beyond the Lambertian Assumption: A generative model for Apparent BRDF fields of Faces using Anti-Symmetric Tensor Splines

Beyond the Lambertian Assumption: A generative model for App...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.11

作者： Angelos Barmpoutis Ritwik Kumar Baba C. Vemuri Arunava Banerjee Department of Computer and Information Science and Engineering University of Florida USA

Human faces are neither exactly Lambertian nor entirely convex and hence most models in literature which make the Lambertian assumption, fall short when dealing with specularities and cast shadows. In this paper, we present a novel anti-symmetric tensor spline (a spline for tensor-valued functions) based method for the estimation of the Apparent BRDF (ABRDF) field for human faces that seam-lessly accounts for specularities and cast shadows. Furthermore, unlike other methods, it does not require any 3D information to build the model and can work with as few as 9 images. In order to validate the accuracy of our anti-symmetric tensor spline model, we present a novel approximation of the ABRDF using a continuous mixture of single-lobed spherical functions. We demonstrate the effectiveness of our anti-symmetric tensor-spline model in comparison to other popular models in the literature, by presenting extensive results for face relighting and face recognition using the Extended Yale B database.

关键词： Tensile stress Humans Lighting Rendering (computer graphics) Image databases Shape control Information science Face detection Face recognition Graphics

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Image Segmentation via Convolution of a Level-Set Function with a Rigaut Kernel

Image Segmentation via Convolution of a Level-Set Function w...

引用

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

作者： Ozlem N. Subakan Baba C. Vemuri Department of Computer and Information Science and Engineering University of Florida Gainesville FL USA

Image segmentation is a fundamental task in computer vision and there are numerous algorithms that have been successfully applied in various domains. there are still plenty of challenges to be met with. In this paper, we consider one such challenge, that of achieving segmentation while preserving complicated and detailed features present in the image, be it a gray level or a textured image. We present a novel approach that does not make use of any prior information about the objects in the image being segmented. Segmentation is achieved using local orientation information, which is obtained via the application of a steerable Gabor filter bank, in a statistical framework. this information is used to construct a spatially varying kernel called the Rigaut Kernel, which is then convolved with the signed distance function of an evolving contour (placed in the image) to achieve segmentation. We present numerous experimental results on real images, including a quantitative evaluation. Superior performance of our technique is depicted via comparison to the state-of-the-art algorithms in literature.

关键词： Image segmentation Convolution Kernel Gabor filters Active contours computer vision Context modeling Solid modeling Level set Layout

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