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Statistics of real-world illumination

Statistics of real-world illumination

引用

conference on computer Vision and pattern recognition (CVPR)

作者： R.O. Dror T.K. Leung E.H. Adelson A.S. Willsky Artificial Intelligence Laboratory and Laboratory for Information and Decision Systems Massachusetts Institute of Technology USA

ISBN: (纸本)0769512720

While computer vision systems often assume simple illumination models, real-world illumination is highly complex, consisting of reflected light from every direction as well as distributed and localized primary light sources. One can capture the illumination incident at a point in the real world from every direction photographically using a spherical illumination map. This paper illustrates, through analysis of photographically-acquired, high dynamic range illumination maps, that real-world illumination shares many of the statistical properties of natural images. In particular, the marginal and joint wavelet coefficient distributions, directional derivative distributions, and harmonic spectra of illumination maps resemble those documented in the natural image statistics literature. However, illumination maps differ from standard photographs in that illumination maps are statistically non-stationary and may contain localized light sources that dominate their power spectra. Our work provides a foundation for statistical models of real-world illumination that may facilitate robust estimation of shape, reflectance, and illumination from images.

关键词： Statistics Lighting Statistical distributions Light sources computer vision image analysis Dynamic range Wavelet coefficients Robustness Shape

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Rethinking classical internal forces for active contour models

Rethinking classical internal forces for active contour mode...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： D.P. Perrin C.E. Smith Computer Science and Engineering University of Minnesota Minneapolis MN USA Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

ISBN: (纸本)0769512720

The classical active contour model has two basic internal forces: tension and curvature. These forces are included to provide cohe sion, equal control point spacing, and locally smooth shape. These classical internal forces have undesirable attributes that are in conflict with these original desired characteristics. Tension evenly spaces the control points, but also causes the models to collapse in weak image gradients. Curvature produces locally smooth curvature, but it does so by forcing the model toward a straight line. The paper returns to the original active contour model motivations to reformulate these internal forces. The desired properties are achieved without the introduction of unwanted model behavior A new spacing force and a new constant change in curvature force are introduced and their performance characteristics are discussed. The paper includes experimental results that demonstrate the efficacy and performance of the proposed reformulations.

关键词： Active contours Shape control computer science Force control computer vision Force measurement Pressure measurement Merging Deformable models

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Houghing the Hough: peak collection for detection of corners, junctions and line intersections

Houghing the Hough: peak collection for detection of corners...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： W.A. Barrett K.D. Petersen Department of Computer Science Brigham Young University USA

ISBN: (纸本)0769512720

We exploit the Accumulator Array of the Hough Transform by finding collections of (2 or more) peaks through which a given sinusoid will pass. Such sinusoids identify points in the original image where lines intersect. Peak collection (or line aggregation) is performed by making a second pass through the edge map, but instead of laying points down in the accumulator array (as with the original Hough Transform), we compute the line integral over each sinusoid that corresponds to the current edge point. If a sinusoid passes through /spl ges/2 peaks, we deposit that sum/integral into a new accumulator array - an array that has a direct one-to-one correspondence with the original image. Thus, "Houghing the Hough" identifies points that correspond to corners, junctions or line intersections in image space. During initial peak collection, we include in the line integral only the most (locally) significant peaks while sifting out other (comparatively) weaker peaks from the current as well as subsequent peak collections. This "contextual peak sifting" greatly reduces computation, the effect of noise and the occurrence of false positives. Virtual line intersections (vanishing points, occluded corners, etc.) are detected as peaks without proximate edge support. Results in real-world images show the technique performs well in identifying corners, junctions and intersecting lines in a variety of scenes containing manmade objects such as buildings, documents, etc.

关键词： image edge detection image segmentation Voting Layout Shape computer science Noise reduction Object detection Object recognition Termination of employment

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Grouping connected components using minimal path techniques. Application to reconstruction of vessels in 2D and 3D images

Grouping connected components using minimal path techniques....

引用

conference on computer Vision and pattern recognition (CVPR)

作者： L.D. Cohen T. Deschamps CEREMADE UMR CNRS 7534 Université de Paris IX Dauphine Paris France Medical Imaging Systems Group Philips Research France Suresnes France

ISBN: (纸本)0769512720

We address the problem of finding a set of contour curves in a 2D or 3D image. We consider the problem of perceptual grouping and contour completion, where the data is an unstructured set of regions in the image. A new method to find complete curves from a set of edge points is presented. Contours, are found as minimal paths between connected components, using the fast marching algorithm. We find the minimal paths between each of these components, until the complete set of these "regions" is connected. The paths are obtained using backpropagation from the saddle points to both components. We then extend this technique to 3D. The data is a set of connected components in a 3D image. We find 3D minimal paths that link together these components. Using a potential based on vessel detection, we illustrate the capability of our approach to reconstruct tree structures in a 3D medical image dataset.

关键词： image reconstruction Object detection Biomedical imaging Active contours Backpropagation algorithms Tree data structures Level set Topology Shape Humans

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A spherical eye from multiple cameras (makes better models of the world)

A spherical eye from multiple cameras (makes better models o...

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conference on computer Vision and pattern recognition (CVPR)

作者： P. Baker C. Fermuller Y. Aloimonos R. Pless Computer Vision Laboratory University of Maryland College Park MD USA Department of Computer Science Washington University Saint Louis MO USA

ISBN: (纸本)0769512720

The paper describes an imaging system that has been designed specifically for the purpose of recovering egomotion and structure from video. The system consists of six cameras in a network arranged so that they sample different parts of the visual sphere. This geometric configuration has provable advantages compared to small field of view cameras for the estimation of the system's own motion and consequently the estimation of shape models from the individual cameras. The reason is that inherent ambiguities of confusion between translation and rotation disappear. We provide algorithms for the calibration of the system and 3D motion estimation. The calibration is based on a new geometric constraint that relates the images of lines parallel in space to the rotation between the cameras. The 3D motion estimation uses a constraint relating structure directly to image gradients.

关键词： Cameras Motion estimation Shape Layout Calibration Space technology Robot vision systems Pixel computer vision Laboratories

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Scalable, absolute position recovery for omni-directional image networks

Scalable, absolute position recovery for omni-directional im...

引用

conference on computer Vision and pattern recognition (CVPR)

作者： M. Antone S. Teller MIT Computer Graphics Group USA

ISBN: (纸本)0769512720

We describe a linear-time algorithm that recovers absolute camera positions for networks of thousands of terrestrial images spanning hundreds of meters in outdoor urban scenes, under uncontrolled lighting. The algorithm requires no human input or interaction. For real data, it recovers camera pose globally consistent on average to roughly five centimeters, or about four pixels of epipolar alignment. The paper's principal contributions include an extension of Markov chain Monte Carlo estimation techniques to the case of unknown numbers of feature points, unknown occlusion and deocclusion, large scale (thousands of images, and hundreds of thousands of point features), and large dimensional extent (tens of meters of inter-camera baseline, and hundreds of meters of baseline overall). Also, a principled method is given to manage uncertainty on the sphere; a new use of the Hough transform is proposed; and a method for aggregating local baseline constraints into a globally consistent pose set is described.

关键词： Cameras Layout computer graphics Humans Monte Carlo methods computer vision Robustness Inference algorithms Large-scale systems Uncertainty

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Two-body segmentation from two perspective views

Two-body segmentation from two perspective views

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conference on computer Vision and pattern recognition (CVPR)

作者： L. Wolf A. Shashua School of Computer Science and Engineering Hebrew University Jerusalem Israel Computer Science Department University of Stanford USA

ISBN: (纸本)0769512720

We consider a scene containing two independently and generally moving objects, viewed by two general perspective views. Using matching points arising from both objects simultaneously we derive a geometrical constraint, applicable to points from both objects, we call the segmentation matrix. We then use this constraint in order to recover the fundamental matrices associated with, each object, or simply to segment the scene into the two objects. Moreover, when the two bodies move in pure translation relative to each other we can both segment the scene and recover the affine calibration (homography at infinity) of the camera geometry. Unlike algorithms suggested in the past we need only two images, we work with general projective cameras (rather than affine or orthographic) and with general body motion, and no prior information beyond point matches is required.

关键词： image segmentation Layout Cameras computer science Calibration Symmetric matrices H infinity control Impedance matching Geometry Solid modeling

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An open problem in matching sets of 3D lines

An open problem in matching sets of 3D lines

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conference on computer Vision and pattern recognition (CVPR)

作者： B. Kamgar-Parsi Advanced IT Branch Naval Research Laboratory Washington DC

ISBN: (纸本)0769512720

Methods for matching sets of 3D lines depend on whether line lengths are finite or infinite. In terms of line lengths, three basic cases arise in matching sets of lines: (1) finite to finite, (2) finite to infinite, and (3) infinite to infinite. For cases 1 and 2, which have not been treated in the literature, we present convergent iterative algorithms that (almost) always find the best match. For case 3, O.D. Faugeras and M. Hebert (FH) (1986) have proposed a popular iterative method that cannot be guaranteed to converge. We present an alternative approach that does converge. However, we also show that neither the FH solution, nor our solution is invariant with respect to coordinate transforms, which renders any best match meaningless. Thus, a satisfactory solution to case 3 does not yet exist. We discuss the underlying problem, which is the representation of infinite lines, and suggest alternatives that may lead to an invariant solution.

关键词： image segmentation Iterative methods image edge detection Laboratories Iterative algorithms computer vision Application software Layout Motion estimation Government

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Flexible flow for 3D nonrigid tracking and shape recovery

Flexible flow for 3D nonrigid tracking and shape recovery

引用

conference on computer Vision and pattern recognition (CVPR)

作者： M. Brand R. Bhotika Mitsubishi Electric Research Laboratories Inc. Cambridge MA USA University of Rochester Computer Science Rochester NY USA

ISBN: (纸本)0769512720

We introduce linear methods for model-based tracking of nonrigid 3D objects and for acquiring such models from video. 3D motions and flexions are calculated directly from image intensities without information-lossy intermediate results. Measurement uncertainty is quantified and fully propagated through the inverse model to yield posterior mean (PM) and/or mode (MAP) pose estimates. A Bayesian framework manages uncertainty, accommodates priors, and gives confidence measures. We obtain highly accurate and robust closed-form estimators by minimizing information loss from non-reversible (inner-product and least-squares) operations, and, when unavoidable, performing such operations with the appropriate error norm. For model acquisition, we show how to refine a crude or generic model to fit the video subject. We demonstrate with tracking, model refinement, and super-resolution texture lifting from low-quality low-resolution video.

关键词： Shape Robustness Inverse problems Measurement uncertainty Yield estimation Bayesian methods image motion analysis Error correction Matrices Delay estimation

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Stability issues in recovering illumination distribution from brightness in shadows

Stability issues in recovering illumination distribution fro...

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conference on computer Vision and pattern recognition (CVPR)

作者： I. Sato Y. Sato K. Ikeuchi Institute of Industrial Science University of Tokyo Japan

ISBN: (纸本)0769512720

The paper describes a robust method for estimating, in a reliable manner, the illumination distribution of a real scene from shadows in a given image. In general, shadows in a scene are caused by the occlusion of incoming light; image brightness inside shadows have great potential for providing distinct clues to the illumination distribution of the scene. Taking advantage of this fact, we recently proposed to estimate the illumination distribution of a real scene from a single image of the scene. The proposed method has been applied successfully to real images with complex illumination distributions. Nevertheless, it was found that sometimes the method failed to provide a correct estimate of illumination distribution. Those failures stem from the fact that the method does not take into account several factors regarding the stability of illumination estimation. The study analyzes how much information is obtainable from a given image about the illumination distribution of the scene. In particular, we carefully examine the source of instability of using shadows obtained from a single image for the estimation in several aspects: blocked view of shadows by the object; limited sampling resolution for image brightness inside shadows; and the appropriate light model to approximate the illumination distribution of the scene. Based on this analysis, we propose a method that guarantees to reliably estimate the illumination distribution of a scene, regardless of the type of input image.

关键词： Stability Lighting Brightness Layout Shape Reflectivity image analysis Robustness Cameras Light sources

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