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A novel convergence scheme for active appearance models

A novel convergence scheme for active appearance models

引用

conference on computer Vision and pattern recognition (CVPR)

作者： A. Umit Batur H.H. Monson School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA Georgia Institute of Technology Atlanta GA US Sch. of Electr. & Comput. Eng. Georgia Inst. of Technol. Atlanta GA USA

The active appearance model (AAM) algorithm is a powerful tool for modeling images of deformable objects. AAM combines a subspace-based deformable model of an object's appearance with a fast and robust method of fitting this model to a previously unseen image. The speed of this algorithm comes from the assumption that the gradient matrix is fixed around the optimal coefficients for all images. In this paper, we propose a convergence scheme for AAM that adapts this gradient matrix to the target image's texture during convergence by adding linear modes of change that are based on the texture eigenvectors of AAM. We show that this adaptive strategy for the gradient matrix provides a significant increase in the performance of the AAM algorithm.

关键词： Convergence Active appearance model Shape Principal component analysis Deformable models Robustness Power engineering computing Power engineering and energy Target tracking Face recognition

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Implicit meshes for modeling and reconstruction

Implicit meshes for modeling and reconstruction

引用

conference on computer Vision and pattern recognition (CVPR)

作者： S. Ilic P. Fua Computer Vision Laboratory EPF Lausanne Switzerland

Explicit surfaces, such as triangulations or wireframe models, have been extensively used to represent the deformable 3D models that are used to fit 3D point and 2D silhouette data. The resulting approaches, however, suffer from the fact that fitting typically involves finding the facets that are closest to the 3D data points or most likely to be silhouette facets. This requires searching, which is slow, and dealing with the non-differentiability of the distance function. By contrast, implicit surface representations allow fitting without search, since one can simply evaluate a differentiable field function at every data point. However, implicit representations are not necessarily the most intuitive ones and users, such as graphics designers, tend to prefer explicit models.

关键词： Surface fitting Deformable models computer vision Surface reconstruction Graphics Displacement control image reconstruction Video sequences Shape control Laboratories

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Shape context and chamfer matching in cluttered scenes

Shape context and chamfer matching in cluttered scenes

引用

conference on computer Vision and pattern recognition (CVPR)

作者： A. Thayananthan B. Stenger P.H.S. Torr R. Cipolla Department of Engineering University of Cambridge Cambridge UK Microsoft Research Limited Cambridge UK

This paper compares two methods for object localization from contours: shape context and chamfer matching of templates. In the light of our experiments, we suggest improvements to the shape context: shape contexts are used to find corresponding features between model and image. In real images it is shown that the shape context is highly influenced by clutters; furthermore, even when the object is correctly localized, the feature correspondence may be poor. We show that the robustness of shape matching can be increased by including a figural continuity constraint. The combined shape and continuity cost is minimized using the Viterbi algorithm on features, resulting in improved localization and correspondence. Our algorithm can be generally applied to any feature based shape matching method. Chamfer matching correlates model templates with the distance transform of the edge image. This can be done efficiently using a coarse-to-fine search over the transformation parameters. The method is robust in clutter, however, multiple templates are needed to handle scale, rotation and shape variation. We compare both methods for locating hand shapes in cluttered images, and applied to word recognition in EZ-Gimpy images.

关键词： Shape Layout computer vision Robustness Context modeling Costs Viterbi algorithm image recognition Geometry image segmentation

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Pose reconstruction with an uncalibrated computed tomography imaging

Pose reconstruction with an uncalibrated computed tomography...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： Maurin B C. Doignon M. de Mathelin A. Gangi LSIIT (UMR CNRS 7005) Strasbourg University Illkirch-Graffenstaden France Department of Radiology B University Hospital of Strasbourg Strasbourg France

In this paper, we address the problem of precisely recovering the 3D (three-dimensional) pose of 3D shape fiducials from images obtained by means of an uncalibrated computed tomography (CT) imaging device. The main goal in this work is to model and estimate the geometric transformation relating line fiducials to their projections in cross-sectional images. To do so, we propose techniques, which solve the points to lines correspondence using closed-form and numerical algorithms. A geometric transformation with eight degrees of freedom (rotation, translation and anisotropic scaling) is used to model both a rigid-body transformation and a scaling transformation accounting for CT scan intrinsic parameters. Furthermore, an estimation of error bounds in space is given when image data are affected by noise. Real experiments show that the proposed method provides good results on a set of CT images from many viewpoints.

关键词： image reconstruction Computed tomography Orbital robotics Hospitals Solid modeling Anisotropic magnetoresistance Parameter estimation Surgery Magnetic resonance imaging image generation

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Resolution vs. tracking error: zoom as a gain controller

Resolution vs. tracking error: zoom as a gain controller

引用

conference on computer Vision and pattern recognition (CVPR)

作者： B.J. Tordoff D.W. Murray Department of Engineering Science University of Oxford Oxford UK

During tracking, lens zoom acts as a gain between scene dynamics and fixation errors, providing a trade-off between maximizing resolution and minimizing tracking error. Using a linear Kalman filter model, it is shown that when image measurement error scales with focal length, the filter is invariant to zoom. When the error is of fixed size, however, zooming alters the balance between process and measurement errors in a counter-intuitive manner. It is shown that this balance can be restored by appropriate adjustment of the process noise. With a zoom invariant filter, zoom can be used to ensure that fixation errors remain bounded. To this end, an error variance control method is proposed which gives high confidence that the target will not leave the image during tracking. To implement such a scheme, equipment delays and responses must be known, including those of the zoom lenses. Experiments to measure these are described, and overall results are presented for 30 Hz tracking of real scenes.

关键词： Error correction Lenses Cameras Layout Filters Measurement errors image restoration Target tracking Delay Angular velocity

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Learning epipolar geometry from image sequences

Learning epipolar geometry from image sequences

引用

conference on computer Vision and pattern recognition (CVPR)

作者： Y. Wexler A.W. Fitzgibbon A. Zisserman Visual Geometry Group Department of Engineering Science University of Oxford UK

We wish to determine the epipolar geometry of a stereo camera pair from image measurements alone. This paper describes a solution to this problem, which does not require a parametric model of the camera system, and consequently applies equally well to a wide class of stereo configurations. Examples in the paper range from a standard pinhole stereo configuration to more exotic systems combining curved mirrors and wide-angle lenses. The method described here allows epipolar curves to be learnt from multiple image pairs acquired by stereo cameras with fixed configuration. By aggregating information over the multiple image pairs, a dense map of the epipolar curves can be determined on the images. The algorithm requires a large number of images, but has the distinct benefit that the correspondence problem does not have to be explicitly solved. We show that for standard stereo configurations the results are comparable to those obtained from a state of the art parametric model method, despite the significantly weaker constraints on the non-parametric model. The new algorithm is simple to implement, so it may easily be employed on a new and possibly complex camera system.

关键词： image sequences Cameras Parametric statistics Stereo vision Mirrors Lenses Computational geometry Solid modeling Optical distortion Optical noise

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Extracting dense features for visual correspondence with graph cuts

Extracting dense features for visual correspondence with gra...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： O. Veksler NEC Laboratories of America Inc. Princeton NJ USA

We present a method for extracting dense features from stereo and motion sequences. Our dense feature is defined symmetrically with respect to both images, and it is extracted during the correspondence process, not in a separate preprocessing.step. For dense feature extraction we use the graph cuts algorithm, recently shown to be a powerful optimization tool for vision. Our algorithm produces semi-dense answer, with very accurate results in areas where features are detected, and no matches in featureless regions. Unlike sparse feature based algorithms, we are able to extract accurate correspondences in some untextured regions, provided that there are texture cues on the boundary. Our algorithm is robust and does not require parameter tuning.

关键词： Feature extraction Pixel Layout Robustness Optical noise Boundary conditions National electric code Laboratories computer vision image motion analysis

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Illumination normalization with time-dependent intrinsic images for video surveillance

Illumination normalization with time-dependent intrinsic ima...

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conference on computer Vision and pattern recognition (CVPR)

作者： Y. Matsushita K. Nishino K. Ikeuchi M. Sakauchi Institute of Industrial Science University of Tokyo Tokyo Japan Department of Computer Science Columbia University NY USA

Cast shadows produce troublesome effects for video surveillance systems, typically for object tracking from a fixed viewpoint, since it yields appearance variations of objects depending on whether they are inside or outside the shadow. To robustly eliminate these shadows from image sequences as a preprocessing.stage for robust video surveillance, we propose a framework based on the idea of intrinsic images. Unlike previous methods for deriving intrinsic images, we derive time-varying reflectance images and corresponding illumination images from a sequence of images. Using obtained illumination images, we normalize the input image sequence in terms of incident lighting distribution to eliminate shadow effects. We also propose an illumination normalization scheme, which can potentially run in real time, utilizing the illumination eigenspace, which captures the illumination variation due to weather, time of day etc., and a shadow interpolation method based on shadow hulls. This paper describes the theory of the framework with simulation results, and shows its effectiveness with object tracking results on real scene data sets for traffic monitoring.

关键词： Lighting Video surveillance Robustness image sequences Layout Target tracking Reflectivity Interpolation Buildings image databases

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The effects of segmentation and feature choice in a translation model of object recognition

The effects of segmentation and feature choice in a translat...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： K. Barnard P. Duygulu R. Guru P. Gabbur D. Forsyth Department of Computing Science University of Arizona Tucson USA Computer Science Division University of California Berkeley USA

We work with a model of object recognition where words must be placed on image regions. This approach means that large scale experiments are relatively easy, so we can evaluate the effects of various early and midlevel vision algorithms on recognition performance. We evaluate various image segmentation algorithms by determining word prediction accuracy for images segmented in various ways and represented by various features. We take the view that good segmentations respect object boundaries, and so word prediction should be better for a better segmentation. However, it is usually very difficult in practice to obtain segmentations that do not break up objects, so most practitioners attempt to merge segments to get better putative object representations. We demonstrate that our paradigm of word prediction easily allows us to predict potentially useful segment merges, even for segments that do not look similar (for example, merging the black and white halves of a penguin is not possible with feature-based segmentation; the main cue must be "familiar configuration"). These studies focus on unsupervised learning of recognition. However, we show that word prediction can be markedly improved by providing supervised information for a relatively small number of regions together with large quantities of unsupervised information. This supervisory information allows a better and more discriminative choice of features and breaks possible symmetries.

关键词： Object recognition Probability distribution Labeling computer vision Shape Frequency Gaussian processes computer science computer society pattern recognition

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Toward a stratification of Helmholtz stereopsis

Toward a stratification of Helmholtz stereopsis

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conference on computer Vision and pattern recognition (CVPR)

作者： T.E. Zickler P.N. Belhumeur D.J. Kriegman Electrical Engineering Yale University New Heaven CT USA Computer Science Columbia University New York NY USA Computer Science and Engineering University of California San Diego La Jolla CA USA

Helmholtz stereopsis has been previously introduced as a surface reconstruction technique that does not assume a model of surface reflectance. This technique relies on the use of multiple cameras and light sources, and it has been shown to be effective when the camera and source positions are known. Here, we take a stratified look at uncalibrated Helmholtz stereopsis. We derive a photometric matching constraint that can be used to establish correspondence without any knowledge of the cameras and sources (except that they are co-located), and we determine conditions under which we can obtain affine and metric reconstructions. An implementation and experimental results are presented.

关键词： Cameras Photometry Lighting Stereo vision Light sources image reconstruction Surface reconstruction Reflectivity Shape computer society

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