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164
A comparison and evaluation of multiview stereo reconstruction algorithms.
 In Proc. Computer Vision and Pattern Recognition ’06,
, 2006
"... Abstract This paper presents a quantitative comparison of several multiview stereo reconstruction algorithms. Until now, the lack of suitable calibrated multiview image datasets with known ground truth (3D shape models) has prevented such direct comparisons. In this paper, we first survey multiv ..."
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Cited by 530 (14 self)
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Abstract This paper presents a quantitative comparison of several multiview stereo reconstruction algorithms. Until now, the lack of suitable calibrated multiview image datasets with known ground truth (3D shape models) has prevented such direct comparisons. In this paper, we first survey multiview stereo algorithms and compare them qualitatively using a taxonomy that differentiates their key properties. We then describe our process for acquiring and calibrating multiview image datasets with highaccuracy ground truth and introduce our evaluation methodology. Finally, we present the results of our quantitative comparison of stateoftheart multiview stereo reconstruction algorithms on six benchmark datasets. The datasets, evaluation details, and instructions for submitting new models are available online at http://vision.middlebury.edu/mview.
Image alignment and stitching: a tutorial
, 2006
"... This tutorial reviews image alignment and image stitching algorithms. Image alignment algorithms can discover the correspondence relationships among images with varying degrees of overlap. They are ideally suited for applications such as video stabilization, summarization, and the creation of panora ..."
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Cited by 115 (2 self)
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This tutorial reviews image alignment and image stitching algorithms. Image alignment algorithms can discover the correspondence relationships among images with varying degrees of overlap. They are ideally suited for applications such as video stabilization, summarization, and the creation of panoramic mosaics. Image stitching algorithms take the alignment estimates produced by such registration algorithms and blend the images in a seamless manner, taking care to deal with potential problems such as blurring or ghosting caused by parallax and scene movement as well as varying image exposures. This tutorial reviews the basic motion models underlying alignment and stitching algorithms, describes effective direct (pixelbased) and featurebased alignment algorithms, and describes blending algorithms used to produce
Realtime markerless tracking for augmented reality: the virtual visual servoing framework
 IEEE TRANS. ON VISUALIZATION AND COMPUTER GRAPHICS
, 2006
"... Tracking is a very important research subject in a realtime augmented reality context. The main requirements for trackers are high accuracy and little latency at a reasonable cost. In order to address these issues, a realtime, robust, and efficient 3D modelbased tracking algorithm is proposed for ..."
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Cited by 114 (29 self)
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Tracking is a very important research subject in a realtime augmented reality context. The main requirements for trackers are high accuracy and little latency at a reasonable cost. In order to address these issues, a realtime, robust, and efficient 3D modelbased tracking algorithm is proposed for a “video see through ” monocular vision system. The tracking of objects in the scene amounts to calculating the pose between the camera and the objects. Virtual objects can then be projected into the scene using the pose. Here, nonlinear pose estimation is formulated by means of a virtual visual servoing approach. In this context, the derivation of pointtocurves interaction matrices are given for different 3D geometrical primitives including straight lines, circles, cylinders, and spheres. A local moving edges tracker is used in order to provide realtime tracking of points normal to the object contours. Robustness is obtained by integrating an Mestimator into the visual control law via an iteratively reweighted least squares implementation. This approach is then extended to address the 3D modelfree augmented reality problem. The method presented in this paper has been validated on several complex image sequences including outdoor environments. Results show the method to be robust to occlusion, changes in illumination, and mistracking.
Fast image deconvolution using hyperlaplacian priors, supplementary material
, 2009
"... The heavytailed distribution of gradients in natural scenes have proven effective priors for a range of problems such as denoising, deblurring and superresolution. These distributions are well modeled by a hyperLaplacian p(x) ∝ e−kxα), typically with 0.5 ≤ α ≤ 0.8. However, the use of sparse ..."
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Cited by 109 (2 self)
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The heavytailed distribution of gradients in natural scenes have proven effective priors for a range of problems such as denoising, deblurring and superresolution. These distributions are well modeled by a hyperLaplacian p(x) ∝ e−kxα), typically with 0.5 ≤ α ≤ 0.8. However, the use of sparse distributions makes the problem nonconvex and impractically slow to solve for multimegapixel images. In this paper we describe a deconvolution approach that is several orders of magnitude faster than existing techniques that use hyperLaplacian priors. We adopt an alternating minimization scheme where one of the two phases is a nonconvex problem that is separable over pixels. This perpixel subproblem may be solved with a lookup table (LUT). Alternatively, for two specific values of α, 1/2 and 2/3 an analytic solution can be found, by finding the roots of a cubic and quartic polynomial, respectively. Our approach (using either LUTs or analytic formulae) is able to deconvolve a 1 megapixel image in less than ∼3 seconds, achieving comparable quality to existing methods such as iteratively reweighted least squares (IRLS) that take ∼20 minutes. Furthermore, our method is quite general and can easily be extended to related image processing problems, beyond the deconvolution application demonstrated. 1
The dualbootstrap iterative closest point algorithm with application to retinal image registration
 IEEE Trans. Med. Img
, 2003
"... Abstract—Motivated by the problem of retinal image registration, this paper introduces and analyzes a new registration algorithm called DualBootstrap Iterative Closest Point (DualBootstrap ICP). The approach is to start from one or more initial, loworder estimates that are only accurate in small ..."
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Cited by 88 (19 self)
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Abstract—Motivated by the problem of retinal image registration, this paper introduces and analyzes a new registration algorithm called DualBootstrap Iterative Closest Point (DualBootstrap ICP). The approach is to start from one or more initial, loworder estimates that are only accurate in small image regions, called bootstrap regions. In each bootstrap region, the algorithm iteratively: 1) refines the transformation estimate using constraints only from within the bootstrap region; 2) expands the bootstrap region; and 3) tests to see if a higher order transformation model can be used, stopping when the region expands to cover the overlap between images. Steps 1): and 3), the bootstrap steps, are governed by the covariance matrix of the estimated transformation. Estimation refinement [Step 2)] uses a novel robust version of the ICP algorithm. In registering retinal image pairs, DualBootstrap ICP is initialized by automatically matching individual vascular landmarks, and it aligns images based on detected blood vessel centerlines. The resulting quadratic transformations are accurate to less than a pixel. On tests involving approximately 6000 image pairs, it successfully registered 99.5 % of the pairs containing at least one common landmark, and 100 % of the pairs containing at least one common landmark and at least 35 % image overlap. Index Terms—Iterative closest point, medical imaging, registration, retinal imaging, robust estimation.
A featurebased, robust, hierarchical algorithm for registering pairs of images of the curved human retina
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2002
"... AbstractÐThis paper describes a robust hierarchical algorithm for fullyautomatic registration of a pair of images of the curved human retina photographed by a fundus microscope. Accurate registration is essential for mosaic synthesis, change detection, and design of computeraided instrumentation. ..."
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Cited by 68 (18 self)
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AbstractÐThis paper describes a robust hierarchical algorithm for fullyautomatic registration of a pair of images of the curved human retina photographed by a fundus microscope. Accurate registration is essential for mosaic synthesis, change detection, and design of computeraided instrumentation. Central to the newalgorithm is a 12parameter interimage transformation derived by modeling the retina as a rigid quadratic surface with unknown parameters, imaged by an uncalibrated weak perspective camera. The parameters of this model are estimated by matching vascular landmarks extracted by an algorithm that recursively traces the blood vessel structure. The parameter estimation technique, which could be generalized to other applications, is a hierarchy of models and methods: an initial match set is pruned based on a zeroth order transformation estimated as the peak of a similarityweighted histogram; a first order, affine transformation is estimated using the reduced match set and leastmedian of squares; and the final, second order, 12parameter transformation is estimated using an Mestimator initialized from the first order estimate. This hierarchy makes the algorithm robust to unmatchable image features and mismatches between features caused by large interframe motions. Before final convergence of the Mestimator, feature positions are refined and the correspondence set is enhanced using normalized sumofsquared differences matching of regions deformed by the emerging transformation. Experiments involving 3,000 image pairs �1; 024 1; 024 pixels) from 16 different healthy eyes were performed. Starting with as low as 20 percent overlap between images, the algorithm improves its success rate exponentially and has a negligible failure rate above 67 percent overlap. The experiments also quantify the reduction in errors as the model complexities increase. Final registration errors less than a pixel are routinely achieved. The speed, accuracy, and
Estimation of subspace arrangements with applications in modeling and segmenting mixed data
, 2006
"... Abstract. Recently many scientific and engineering applications have involved the challenging task of analyzing large amounts of unsorted highdimensional data that have very complicated structures. From both geometric and statistical points of view, such unsorted data are considered mixed as differ ..."
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Cited by 60 (4 self)
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Abstract. Recently many scientific and engineering applications have involved the challenging task of analyzing large amounts of unsorted highdimensional data that have very complicated structures. From both geometric and statistical points of view, such unsorted data are considered mixed as different parts of the data have significantly different structures which cannot be described by a single model. In this paper we propose to use subspace arrangements—a union of multiple subspaces—for modeling mixed data: each subspace in the arrangement is used to model just a homogeneous subset of the data. Thus, multiple subspaces together can capture the heterogeneous structures within the data set. In this paper, we give a comprehensive introduction to a new approach for the estimation of subspace arrangements. This is known as generalized principal component analysis (GPCA). In particular, we provide a comprehensive summary of important algebraic properties and statistical facts that are crucial for making the inference of subspace arrangements both efficient and robust, even when the given data are corrupted by noise or contaminated with outliers. This new method in many ways improves and generalizes extant methods for modeling or clustering mixed data. There have been successful applications of this new method to many realworld problems in computer vision, image processing, and system identification. In this paper, we will examine several of those representative applications. This paper is intended to be expository in nature. However, in order that this may serve as a more complete reference for both theoreticians and practitioners, we take the liberty of filling in several gaps between the theory and the practice in the existing literature.
Spatiotemporal alignment of sequences
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2002
"... This paper studies the problem of sequencetosequence alignment, namely establishing correspondences in time and in space between two di erent video sequences of the same dynamic scene. The sequences are recorded by uncalibrated video cameras, which are either stationary or jointly moving, with xed ..."
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Cited by 60 (2 self)
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This paper studies the problem of sequencetosequence alignment, namely establishing correspondences in time and in space between two di erent video sequences of the same dynamic scene. The sequences are recorded by uncalibrated video cameras, which are either stationary or jointly moving, with xed (but unknown) internal parameters and relative intercamera external parameters. Temporal variations between image frames (such as moving objects or changes in scene illumination) are powerful cues for alignment, which cannot be exploited by standard imagetoimage alignment techniques. We show that by folding spatial and temporal cues into a single alignment framework, situations which are inherently ambiguous for traditional imagetoimage alignment methods, are often uniquely resolved by sequencetosequence alignment. Furthermore, the ability to align and integrate information across multiple video sequences both in time and in space gives rise to new video applications that are not possible when only imagetoimage alignment is used. 1
A RealTime Tracker For Markerless Augmented Reality
 In ACM/IEEE Int. Symp. on Mixed and Augmented Reality, ISMAR’03
, 2003
"... Augmented Reality has now progressed to the point where realtime applications are being considered and needed. At the same time it is important that synthetic elements are rendered and aligned in the scene in an accurate and visually acceptable way. In order to address these issues a realtime, rob ..."
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Cited by 55 (16 self)
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Augmented Reality has now progressed to the point where realtime applications are being considered and needed. At the same time it is important that synthetic elements are rendered and aligned in the scene in an accurate and visually acceptable way. In order to address these issues a realtime, robust and efficient 3D modelbased tracking algorithm is proposed for a 'video see through' monocular vision system. The tracking of objects in the scene amounts to calculating the pose between the camera and the objects. Virtual objects can then be projected into the scene using the pose. Here, nonlinear pose computation is formulated by means of a virtual visual servoing approach. In this context, the derivation of pointtocurves interaction matrices are given for different features including lines, circles, cylinders and spheres. A local moving edges tracker is used in order to provide realtime tracking of points normal to the object contours. A method is proposed for combining local position uncertainty and global pose uncertainty in an efficient and accurate way by propagating uncertainty. Robustness is obtained by integrating a Mestimator into the visual control law via an iteratively reweighted least squares implementation. The method presented in this paper has been validated on several complex image sequences including outdoor environments. Results show the method to be robust to occlusion, changes in illumination and misstracking. 1.