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207
Shock Graphs and Shape Matching
, 1997
"... We have been developing a theory for the generic representation of 2D shape, where structural descriptions are derived from the shocks (singularities) of a curve evolution process, acting on bounding contours. We now apply the theory to the problem of shape matching. The shocks are organized into a ..."
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Cited by 268 (35 self)
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We have been developing a theory for the generic representation of 2D shape, where structural descriptions are derived from the shocks (singularities) of a curve evolution process, acting on bounding contours. We now apply the theory to the problem of shape matching. The shocks are organized into a directed, acyclic shock graph, and complexity is managed by attending to the most significant (central) shape components first. The space of all such graphs is highly structured and can be characterized by the rules of a shock graph grammar. The grammar permits a reduction of a shock graph to a unique rooted shock tree. We introduce a novel tree matching algorithm which finds the best set of corresponding nodes between two shock trees in polynomial time. Using a diverse database of shapes, we demonstrate our system's performance under articulation, occlusion, and changes in viewpoint.
THIRTY YEARS OF GRAPH MATCHING IN PATTERN RECOGNITION
, 2004
"... A recent paper posed the question: "Graph Matching: What are we really talking about?". Far from providing a definite answer to that question, in this paper we will try to characterize the role that graphs play within the Pattern Recognition field. To this aim two taxonomies are presented ..."
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Cited by 234 (1 self)
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A recent paper posed the question: "Graph Matching: What are we really talking about?". Far from providing a definite answer to that question, in this paper we will try to characterize the role that graphs play within the Pattern Recognition field. To this aim two taxonomies are presented and discussed. The first includes almost all the graph matching algorithms proposed from the late seventies, and describes the different classes of algorithms. The second taxonomy considers the types of common applications of graphbased techniques in the Pattern Recognition and Machine Vision field.
Recognition of Shapes by Editing Their Shock Graphs
 Proc. Int’l Conf. Computer Vision
, 2001
"... Abstract—This paper presents a novel framework for the recognition of objects based on their silhouettes. The main idea is to measure the distance between two shapes as the minimum extent of deformation necessary for one shape to match the other. Since the space of deformations is very highdimensio ..."
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Cited by 204 (8 self)
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Abstract—This paper presents a novel framework for the recognition of objects based on their silhouettes. The main idea is to measure the distance between two shapes as the minimum extent of deformation necessary for one shape to match the other. Since the space of deformations is very highdimensional, three steps are taken to make the search practical: 1) define an equivalence class for shapes based on shockgraph topology, 2) define an equivalence class for deformation paths based on shockgraph transitions, and 3) avoid complexityincreasing deformation paths by moving toward shockgraph degeneracy. Despite these steps, which tremendously reduce the search requirement, there still remain numerous deformation paths to consider. To that end, we employ an editdistance algorithm for shock graphs that finds the optimal deformation path in polynomial time. The proposed approach gives intuitive correspondences for a variety of shapes and is robust in the presence of a wide range of visual transformations. The recognition rates on two distinct databases of 99 and 216 shapes each indicate highly successful within category matches (100 percent in top three matches), which render the framework potentially usable in a range of shapebased recognition applications. Index Terms—Shape deformation, shock graphs, graph matching, edit distance, shape matching, object recognition, dynamic programming. æ 1
Flexible Syntactic Matching of Curves and its Application to Automatic Hierarchical Classification of Silhouettes
 IEEE Transactions on Pattern Analysis and Machine Intelligence
"... Curve matching is one instance of the fundamental correspondence problem. Our exible algorithm is designed to match curves under substantial deformations and arbitrary large scaling and rigid transformations. A syntactic representation is constructed for both curves, and an edit transformation which ..."
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Cited by 131 (2 self)
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Curve matching is one instance of the fundamental correspondence problem. Our exible algorithm is designed to match curves under substantial deformations and arbitrary large scaling and rigid transformations. A syntactic representation is constructed for both curves, and an edit transformation which maps one curve to the other is found using dynamic programming. We present extensive...
Semantic coordination: A new approach and an application
, 2003
"... Abstract. Semantic coordination, namely the problem of finding an agreement on the meaning of heterogeneous semantic models, is one of the key issues in the development of the Semantic Web. In this paper, we propose a new algorithm for discovering semantic mappings across hierarchical classification ..."
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Cited by 117 (20 self)
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Abstract. Semantic coordination, namely the problem of finding an agreement on the meaning of heterogeneous semantic models, is one of the key issues in the development of the Semantic Web. In this paper, we propose a new algorithm for discovering semantic mappings across hierarchical classifications based on a new approach to semantic coordination. This approach shifts the problem of semantic coordination from the problem of computing linguistic or structural similarities (what most other proposed approaches do) to the problem of deducing relations between sets of logical formulae that represent the meaning of concepts belonging to different models. We show how to apply the approach and the algorithm to an interesting family of semantic models, namely hierarchical classifications, and present the results of preliminary tests on two types of hierarchical classifications, web directories and catalogs. Finally, we argue why this is a significant improvement on previous approaches. 1
RASCAL: Calculation of Graph Similarity using Maximum Common Edge Subgraphs
, 2002
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Approximate tree matching and shape similarity
 In Proceedings, 7th International Conference on Computer Vision
, 1999
"... We present a framework for 2D shape contour (silhouette) comparison that can account for stretchings, occlusions and region information. Topological changes due to the original 3D scenarios and articulations are also addressed. To compare the degree of similarity between any two shapes, our approach ..."
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Cited by 68 (1 self)
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We present a framework for 2D shape contour (silhouette) comparison that can account for stretchings, occlusions and region information. Topological changes due to the original 3D scenarios and articulations are also addressed. To compare the degree of similarity between any two shapes, our approach is to represent each shape contour with a free tree structure derived from a shape axis (SA) model, which we have recently proposed. We then use a tree matching scheme to find the best approximate match and the matching cost. To deal with articulations, stretchings and occlusions, three local tree matching operations, merge, cut, and mergeandcut, are introduced to yield optimally approximate matches, which can accommodate not only onetoone but manytomany mappings. The optimization process gives guaranteed globally optimal match efficiently. Experimental results on a variety of shape contours are provided. 1
Replicator Equations, Maximal Cliques, and Graph Isomorphism
, 1999
"... We present a new energyminimization framework for the graph isomorphism problem that is based on an equivalent maximum clique formulation. The approach is centered around a fundamental result proved by Motzkin and Straus in the mid1960s, and recently expanded in various ways, which allows us to fo ..."
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Cited by 64 (12 self)
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We present a new energyminimization framework for the graph isomorphism problem that is based on an equivalent maximum clique formulation. The approach is centered around a fundamental result proved by Motzkin and Straus in the mid1960s, and recently expanded in various ways, which allows us to formulate the maximum clique problem in terms of a standard quadratic program. The attractive feature of this formulation is that a clear onetoone correspondence exists between the solutions of the quadratic program and those in the original, combinatorial problem. To solve the program we use the socalled replicator equations—a class of straightforward continuous and discretetime dynamical systems developed in various branches of theoretical biology. We show how, despite their inherent inability to escape from local solutions, they nevertheless provide experimental results that are competitive with those obtained using more elaborate meanfield annealing heuristics.
A New GraphTheoretic Approach to Clustering, with Applications to Computer Vision
, 2004
"... This work applies cluster analysis as a unified approach for a wide range of vision applications, thereby combining the research domain of computer vision and that of machine learning. Cluster analysis is the formal study of algorithms and methods for recovering the inherent structure within a given ..."
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Cited by 62 (6 self)
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This work applies cluster analysis as a unified approach for a wide range of vision applications, thereby combining the research domain of computer vision and that of machine learning. Cluster analysis is the formal study of algorithms and methods for recovering the inherent structure within a given dataset. Many problems of computer vision have precisely this goal, namely to find which visual entities belong to an inherent structure, e.g. in an image or in a database of images. For example, a meaningful structure in the context of image segmentation is a set of pixels which correspond to the same object in a scene. Clustering algorithms can be used to partition the pixels of an image into meaningful parts, which may correspond to different objects. In this work we focus on the problems of image segmentation and image database organization. The visual entities to consider are pixels and images, respectively. Our first contribution in this work is a novel partitional (flat) clustering algorithm. The algorithm uses pairwise representation, where the visual objects (pixels,
Multiscale Medial Loci and Their Properties
"... Blum's medial axes have great strengths, in principle, in intuitively describing object shape in terms of a quasihierarchy of figures. But it is well known that, derived from a boundary, they are damagingly sensitive to detail in that boundary. The development of notions of spatial scale has le ..."
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Cited by 61 (7 self)
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Blum's medial axes have great strengths, in principle, in intuitively describing object shape in terms of a quasihierarchy of figures. But it is well known that, derived from a boundary, they are damagingly sensitive to detail in that boundary. The development of notions of spatial scale has led to some definitions of multiscale medial axes different from the Blum medial axis that considerably overcame the weakness. Three major multiscale medial axes have been proposed: iteratively pruned trees of Voronoi edges [Ogniewicz 1993, Székely 1996, Näf 1996], shock loci of reactiondiffusion equations [Kimia et al. 1995, Siddiqi & Kimia 1996], and height ridges of medialness (cores) [Fritsch et al. 1994, Morse et al. 1993, Pizer et al. 1998]. These are different from the Blum medial axis, and each has different mathematical properties of generic branching and ending properties, singular transitions, and geometry of implied boundary, and they have different strengths and weaknesses for computing object descriptions from images or from object boundaries. These mathematical properties and computational abilities are laid out and compared and contrasted in this paper.