Results 1  10
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34
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
On aligning curves
 IEEE TPAMI
, 2003
"... We present a novel approach to finding a correspondence (alignment) between two curves. The correspondence is based on a notion of an alignment curve which treats both curves symmetrically. We then define a similarity metric based on the alignment curve using two intrinsic properties of the curve, ..."
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Cited by 133 (4 self)
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We present a novel approach to finding a correspondence (alignment) between two curves. The correspondence is based on a notion of an alignment curve which treats both curves symmetrically. We then define a similarity metric based on the alignment curve using two intrinsic properties of the curve, namely, length and curvature. The optimal correspondence is found by an efficient dynamicprogramming method both for aligning pairs of curve segments and pairs of closed curves, and is effective in the presence of a variety of transformations of the curve. Finally, the correspondence is shown in application to handwritten character recognition, prototype formation, and object recognition, and is potentially useful in other applications such as registration and tracking.
Retrieval by Shape Similarity with Perceptual Distance and Effective Indexing
 IEEE TRANSACTIONS ON MULTIMEDIA
, 2000
"... An important problem in accessing and retrieving visual information is to provide efficient similarity matching in large databases. Though much work is being done on the investigation of suitable perceptual models and the automatic extraction of features, little attention is given to the combination ..."
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Cited by 49 (0 self)
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An important problem in accessing and retrieving visual information is to provide efficient similarity matching in large databases. Though much work is being done on the investigation of suitable perceptual models and the automatic extraction of features, little attention is given to the combination of useful representations and similarity models with efficient index structures. In this paper
Shockbased Indexing into Large Shape Databases
, 2002
"... This paper examines issues arising in applying a previously developed editdistance shock graph matching technique to indexing into large shape databases. This approach compares the shock graph topology and attributes to produce a similarity metric, and results in 100% recognition rate in queryi ..."
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Cited by 38 (4 self)
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This paper examines issues arising in applying a previously developed editdistance shock graph matching technique to indexing into large shape databases. This approach compares the shock graph topology and attributes to produce a similarity metric, and results in 100% recognition rate in querying a database of approximately 200 shapes.
Hierarchical Procrustes matching for shape retrival
 in CVPR
, 2006
"... We introduce Hierarchical Procrustes Matching (HPM), a segmentbased shape matching algorithm which avoids problems associated with purely global or local methods and performs well on benchmark shape retrieval tests. The simplicity of the shape representation leads to a powerful matching algorithm w ..."
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Cited by 36 (2 self)
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We introduce Hierarchical Procrustes Matching (HPM), a segmentbased shape matching algorithm which avoids problems associated with purely global or local methods and performs well on benchmark shape retrieval tests. The simplicity of the shape representation leads to a powerful matching algorithm which incorporates intuitive ideas about the perceptual nature of shape while being computationally efficient. This includes the ability to match similar parts even when they occur at different scales or positions. While comparison of multiscale shape representations is typically based on specific features, HPM avoids the need to extract such features. The hierarchical structure of the algorithm captures the appealing notion that matching should proceed in a global to local direction. 1.
Curves vs Skeletons in Object Recognition
 In IEEE International Conference of Image Processing
, 2001
"... The type of representation used in describing shape can have a significant impact on the effectiveness of a recognition strategy. Shape has been represented by its bounding curve as well as by the medial axis representation which captures the regional interaction of the boundaries. Shape matching wi ..."
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Cited by 33 (1 self)
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The type of representation used in describing shape can have a significant impact on the effectiveness of a recognition strategy. Shape has been represented by its bounding curve as well as by the medial axis representation which captures the regional interaction of the boundaries. Shape matching with the former representation is achieved by curve matching, while the latter is achieved by matching skeletal graphs. In this paper, we compare the effectiveness of these two methods using approaches which we have developed recently for each. The results indicate that skeletal matching involves a higher degree of computational complexity, but is better than curve matching in the presence of articulation or rearrangement of parts. However, when these variations are not present, curve matching is a better strategy due to its lower complexity and roughly equivalent recognition rate.
Robust contour matching via the order preserving assignment problem
 IEEE Trans. on Image Processing
, 2004
"... A common approach to determining corresponding points on two shapes is to compute the cost of each possible pairing of points and solve the assignment problem (weighted bipartite matching) for the resulting cost matrix. We consider the problem of solving for point correspondences when the shapes of ..."
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Cited by 28 (0 self)
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A common approach to determining corresponding points on two shapes is to compute the cost of each possible pairing of points and solve the assignment problem (weighted bipartite matching) for the resulting cost matrix. We consider the problem of solving for point correspondences when the shapes of interest are each defined by a single, closed contour. A modification of the standard assignment problem is proposed whereby the correspondences are required to preserve the ordering of the points induced from the shapes ’ contours. Enforcement of this constraint leads to significantly improved correspondences. Robustness with respect to outliers and shape irregularity is obtained by required only a fraction of feature points to be matched. Furthermore, the minimum matching size may be specified in advance. We present efficient dynamic programming algorithms to solve the proposed optimization problem. Experiments on the Brown and MPEG7 shape databases demonstrate the effectiveness of the proposed method relative to the standard assignment problem. 1
Alignmentbased Recognition of Shape Outlines
 IWVF
, 2001
"... We present a 2D shape recognition and classication method based on matching shape outlines. The correspondence between outlines (curves) is based on a notion of an alignment curve and on a measure of similarity between the intrinsic properties of the curve, namely, length and curvature, and is found ..."
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Cited by 21 (5 self)
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We present a 2D shape recognition and classication method based on matching shape outlines. The correspondence between outlines (curves) is based on a notion of an alignment curve and on a measure of similarity between the intrinsic properties of the curve, namely, length and curvature, and is found by an ecient dynamicprogramming method. The correspondence is used to nd a similarity measure which is used in a recognition system. We explore the strengths and weaknesses of the outlinebased representation by examining the eectiveness of the recognition system on a variety of examples.
Shape retrieval based on distance ratio distribution
, 2002
"... We propose a shapematching algorithm based on a distance ratio distribution (DRD), which is used to measure the regularity of the transformation between the shapes to be compared. The standard deviation of the DRD is used to represent the distribution. Our algorithm is robust to translation, scali ..."
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Cited by 14 (0 self)
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We propose a shapematching algorithm based on a distance ratio distribution (DRD), which is used to measure the regularity of the transformation between the shapes to be compared. The standard deviation of the DRD is used to represent the distribution. Our algorithm is robust to translation, scaling and rotation. We illustrate the effectiveness of our algorithm in the contentbased retrieval of shapes using subsets of the MPEG7 standard database SQUID [31]. The experimental results show the competitiveness of our approach.
Augmenting shape with appearance in vehicle category recognition
 In CVPR
, 2006
"... Shape is an important cue for generic object recognition but can be insufficient without other cues such as object appearance. We explore a number of ways in which the geometric aspects of an object can be augmented with its appearance. The main idea is to construct a dense correspondence between th ..."
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Cited by 14 (2 self)
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Shape is an important cue for generic object recognition but can be insufficient without other cues such as object appearance. We explore a number of ways in which the geometric aspects of an object can be augmented with its appearance. The main idea is to construct a dense correspondence between the interior regions of two shapes based on a shapebased correspondence so that the intensity and gradient distributions can be compared, e.g., using a mutual information paradigm. Three methods for regional alignment are suggested and compared here, based on: (i) propagation of correspondences from the silhouette to parallel curves in the interior, (ii) intersection of line segments anchored on corresponding points on the contour, and (iii) correspondence of shape skeletons. These methods have been implemented and applied to vehicle category recognition from aerial videos under known viewing and illumination conditions. We have constructed a photorealistic synthetic video database to explore the performance of these methods under controlled conditions. We have also tested these algorithms on real video collected for this purpose from a balloon. Our findings indicate that (i) augmenting shape with appearance significantly increases recognition rate, and (ii) the region correspondence induced by the shape skeleton yields the highest performance. 1.