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29
A Survey of Image Registration Techniques
 ACM Computing Surveys
, 1992
"... Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times, from different sensors or from different viewpoints. Over the years, a broad range of techniques have been developed for the various types of data and problems. These ..."
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Cited by 964 (2 self)
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Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times, from different sensors or from different viewpoints. Over the years, a broad range of techniques have been developed for the various types of data and problems. These techniques have been independently studied for several different applications resulting in a large body of research. This paper organizes this material by establishing the relationship between the distortions in the image and the type of registration techniques which are most suitable. Two major types of distortions are distinguished. The first type are those which are the source of misregistration, i.e., they are the cause of the misalignment between the two images. Distortions which are the source of misregistration determine the transformation class which will optimally align the two images. The transformation class in turn influences the general technique that should be taken....
Iterative point matching for registration of freeform curves and surfaces
, 1994
"... A heuristic method has been developed for registering two sets of 3D curves obtained by using an edgebased stereo system, or two dense 3D maps obtained by using a correlationbased stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in ma ..."
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Cited by 659 (7 self)
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A heuristic method has been developed for registering two sets of 3D curves obtained by using an edgebased stereo system, or two dense 3D maps obtained by using a correlationbased stereo system. Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in many practical applications, some a priori knowledge exists which considerably simplifies the problem. In visual navigation, for example, the motion between successive positions is usually approximately known. From this initial estimate, our algorithm computes observer motion with very good precision, which is required for environment modeling (e.g., building a Digital Elevation Map). Objects are represented by a set of 3D points, which are considered as the samples of a surface. No constraint is imposed on the form of the objects. The proposed algorithm is based on iteratively matching points in one set to the closest points in the other. A statistical method based on the distance distribution is used to deal with outliers, occlusion, appearance and disappearance, which allows us to do subsetsubset matching. A leastsquares technique is used to estimate 3D motion from the point correspondences, which reduces the average distance between points in the two sets. Both synthetic and real data have been used to test the algorithm, and the results show that it is efficient and robust, and yields an accurate motion estimate.
AdaptiveFocus Statistical Shape Model for Segmentation of 3D MR Structures
 IEEE Trans. on Medical Imaging
, 2000
"... . This paper presents a deformable model for automatically segmenting objects from volumetric MR images and obtaining point correspondences, using geometric and statistical information in a hierarchical scheme. Geometric information is embedded into the model via an affineinvariant attribute vec ..."
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Cited by 57 (18 self)
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. This paper presents a deformable model for automatically segmenting objects from volumetric MR images and obtaining point correspondences, using geometric and statistical information in a hierarchical scheme. Geometric information is embedded into the model via an affineinvariant attribute vector, which characterizes the geometric structure around each model point from a local to a global level. Accordingly, the model deforms seeking boundary points with similar attribute vectors. This is in contrast to most deformable surface models, which adapt to nearby edges without considering the geometric structure. The proposed model is adaptive in that it initially focuses on the most reliable structures of interest, and subsequently switches focus to other structures as those become closer to their respective targets and therefore more reliable. The proposed techniques have been used to segment boundaries of the ventricles, the caudate nucleus, and the lenticular nucleus from v...
Shape Retrieval Based on Dynamic Programming
 IEEE Transactions on Image Processing
, 2000
"... We propose a shape matching algorithm for deformed shapes based on dynamic programming. Our algorithm is capable of grouping together segments at Corresponding author. Current address is Faculty of Computer Science, Dalhousie University, eem@cs.dal.ca This work was supported by a grant from the Na ..."
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Cited by 34 (1 self)
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We propose a shape matching algorithm for deformed shapes based on dynamic programming. Our algorithm is capable of grouping together segments at Corresponding author. Current address is Faculty of Computer Science, Dalhousie University, eem@cs.dal.ca This work was supported by a grant from the Natural Sciences and Engineering Research Council of Canada. y This work was carriedout while the author was visiting York University. finer scales in order to come up with appropriate correspondences with segments at coarser scales. We illustrate the effectiveness of our algorithm in retrieval of shapes by content on two different twodimensional datasets, one of static hand gesture shapes and another of marine life shapes. We also demonstrate the superiority of our approach over traditional approaches to shape matching and retrieval, such as Fourier descriptors, Geometric and Sequential moments. Our evaluation is based on human relevance judgements following a well established meth...
Bayesian inference on visual grammars by neural nets that optimize
 YALE COMPUTER SCIENCE DEPARTMENT
, 1991
"... We exhibit a systematic way to derive neural nets for vision problems. It involves formulating a vision problem as Bayesian inference or decision on a comprehensive model of the visual domain given by a probabilistic grammar. A key feature of this grammar is the way in which it eliminates model inf ..."
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Cited by 17 (4 self)
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We exhibit a systematic way to derive neural nets for vision problems. It involves formulating a vision problem as Bayesian inference or decision on a comprehensive model of the visual domain given by a probabilistic grammar. A key feature of this grammar is the way in which it eliminates model information, such as object labels, as it produces an image; correspondence problems and other noise removal tasks result. The neural nets that arise most directly are generalized assignment networks. Also there are transformations which naturally yield improved algorithms such as correlation matching in scale space and the Frameville neural nets for highlevel vision. Networks derived this way generally have objective functions with spurious local minima; such minima may commonly be avoided by dynamics that include deterministic annealing, for example recent improvements to Mean Field Theory dynamics. The grammatical method of neural net design allows domain knowledge to enter from all levels of the grammar, including "abstract" levels remote from the final image data, and
Optimal Spline Fitting to Planar Shape
, 1993
"... Parametric spline models are used extensively in representing and coding planar curves. For many applications, it is desirable to be able to derive the spline representation from a set of sample points of the planar shape. The problem we address in this paper is to find a cubic spline model to op ..."
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Cited by 13 (0 self)
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Parametric spline models are used extensively in representing and coding planar curves. For many applications, it is desirable to be able to derive the spline representation from a set of sample points of the planar shape. The problem we address in this paper is to find a cubic spline model to optimally approximate a given planar shape. We solve this problem by treating the control points which define the spline as variables and apply an optimization technique to minimize an error norm so as to find the best locations of the control points. The error norm, which is defined as the total squared distance of the curve sample points from the spline model, reflects the discrepancy between the spline and the original curve. The objective function for the optimization process is the error norm plus a term which ensures convergence to the correct solution. The initial locations of the control points are selected heuristically. We also describe an extension of this method, which allow...
On local matching of freeform curves
 In Proc. BMVC
, 1992
"... Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in many practical applications, some a priori knowledge exists which considerably simplifies the problem. In visual navigation, for example, the motion between successive positions is usually either small ..."
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Cited by 10 (0 self)
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Geometric matching in general is a difficult unsolved problem in computer vision. Fortunately, in many practical applications, some a priori knowledge exists which considerably simplifies the problem. In visual navigation, for example, the motion between successive positions is usually either small or approximately known, but a more precise registration is required for environment modeling. The algorithm described in this paper meets this need. Objects are represented by freeform curves, i.e., arbitrary space curves of the type found in practice. A curve is available in the form of a set of chained points. The proposed algorithm is based on iteratively matching points on one curve to the closest points on the other. A leastsquares technique is used to estimate 3D motion from the point correspondences, which reduces the average distance between curves in the two sets. Both synthetic and real data have been used to test the algorithm, and the results show that it is efficient and robust, and yields an accurate motion estimate.
Affineinvariant image retrieval by correspondence matching of shapes
 Image and Vision Computing
, 1999
"... In this paper, we present an efficient multiscale similarity matching method for shapebased image indexing and retrieval. This method is affineinvariant and stable against noise and shape deformations. Shapes which have undergone mirror reflection can also be retrieved in a unified manner. In thi ..."
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Cited by 9 (3 self)
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In this paper, we present an efficient multiscale similarity matching method for shapebased image indexing and retrieval. This method is affineinvariant and stable against noise and shape deformations. Shapes which have undergone mirror reflection can also be retrieved in a unified manner. In this approach, similarity matching is cast as correspondence matching of two shapes which is then solved by minimizing the matching errors between two feature vectors. Since our feature vectors simultaneously capture both local and global affineinvariant features of shapes, this formulation makes our solution to the correspondence problem very robust. To render the technique suitable for interactive image retrieval, a fast error minimization algorithm for computing correspondence matching is further proposed. Theoretical analysis and experimental results show that multiscale similarity matching allows dissimilar shapes to be filtered out very quickly and the resulting method meets the performance and flexibility needed for contentbased image indexing and retrieval. � 1999 Elsevier Science B.V. All rights reserved.
Efficient Shape Matching and Retrieval at Multiple Scales
, 1999
"... We propose a novel approach for the recognition, clustering and retrieval of shapes. The heart of our methodology is a shape matching algorithm based on dynamic programming, that operates implicitly at multiple scales, but avoids the heavy computational cost of the explicit curvature scale space r ..."
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Cited by 4 (2 self)
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We propose a novel approach for the recognition, clustering and retrieval of shapes. The heart of our methodology is a shape matching algorithm based on dynamic programming, that operates implicitly at multiple scales, but avoids the heavy computational cost of the explicit curvature scale space representation. Our method provides for clustering, visualization and browsing of a data set, as well as for indexing, achieving up to three orders of magnitude speedup over sequential scanning. We illustrate the application of our method to real twodimensional static hand gesture data. We also demonstrate the superiority of our approach over traditional approaches to shape matching and retrieval, such as Fourier descriptors, Geometric and Sequential moments. Our evaluation is based on human relevance judgements following a well established methodology from the information retrieval field. 1 Introduction Object recognition is an important problem in computer vision and has received ...
Structurebased ascii art
 ACM Trans. Graph
, 2010
"... Figure 1: Structurebased ASCII art generated by our method (the input is banquet of Figure 18). Characters were chosen from the set of 95 printable ASCII characters. The wide availability and popularity of textbased communication channels encourage the usage of ASCII art in representing images. ..."
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Cited by 4 (0 self)
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Figure 1: Structurebased ASCII art generated by our method (the input is banquet of Figure 18). Characters were chosen from the set of 95 printable ASCII characters. The wide availability and popularity of textbased communication channels encourage the usage of ASCII art in representing images. Existing tonebased ASCII art generation methods lead to halftonelike results and require high text resolution for display, as higher text resolution offers more tone variety. This paper presents a novel method to generate structurebased ASCII art that is currently mostly created by hand. It approximates the major line structure of the reference image content with the shape of characters. Representing the unlimited image content with the extremely limited shapes and restrictive placement of characters makes this problem challenging. Most existing shape similarity metrics either fail to address the misalignment in realworld scenarios, or are unable to account for the differences in position, orientation and scaling. Our key contribution is a novel alignmentinsensitive shape similarity (AISS) metric that tolerates misalignment of shapes while accounting for the differences in position, orientation and scaling. Together with the constrained deformation approach, we formulate the ASCII art generation as an optimization that minimizes shape dissimilarity and deformation. Convincing results and user study are shown to demonstrate its effectiveness.