R. Veltkamp and M. Hagedoorn. State-of-the-art in Shape Matching. Technical Report UU-CS-1999.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....and other geometric objects that do not have distinct landmarks. In computer vision, a wide literature exists for the problem of matching or aligning objects based on their images, and space limitations do not allow us to do justice to the many valuable contributions. We refer the reader to [40] for a recent survey. A common approach consists of matching collections points organized in graphs or trees (e.g. 23, 12] Belongie et al. 6] propose comparing planar contours based on their shape context. There, points are not bound to represent particular landmarks but are just a ....

R. C. Veltkamp and M. Hagedoorn. State of the art in shape matching. Technical Report UU-CS-1999.

....We restrict polygons to be triangles because triangle meshes are easy to manipulate and efficiently rendered. 2. 2# The Spin Image Representation The problem of determining the similarity of two shapes is a fundamental task in shape based recognition, retrieval, clustering, and classification [13,14]. In general, matching methods are grouped according to their representation of shape: 2D contours, 3D volumes, 3D surfaces, structural models and statistics. Unfortunately, most of the methods for 2D shape matching are not extensible to the 3D case. Nevertheless, a number of methodologies have ....

....to their representation of shape: 2D contours, 3D volumes, 3D surfaces, structural models and statistics. Unfortunately, most of the methods for 2D shape matching are not extensible to the 3D case. Nevertheless, a number of methodologies have been proposed for three dimensional shape matching [14]. For the present work we have chosen the spin image representation [9] This model based representation combines the descriptive nature of global signatures with the robustness to partial views and clutter of local features. The representation allows achieving both object recognition and ....

# Veltkamp, R. C., Hagedoorn, M.: State of the art in shape matching. Technical Report UU-CS-1999-27, Utretch University, the Netherlands, 1999.

....auction companies, search engines and portals. Along with color and texture, widely used in the content based image retrieval community, shape information remains an important, although relatively under exploited, cue for pattern recognition and retrieval purposes in large image database (see [1] for an extensive survey of shape matching in computer vision) Nevertheless, even when color and texture are absent, as in line drawing, the human visual system can recognize objects quite well and can also make efficiently coarse distinctions very quickly. This demonstrates the highly ....

....very quickly. This demonstrates the highly discriminative and descriptive power that is only conveyed by the information modeled by a single shape contour. One shape based approach, commonly used in an automatic image database retrieval system, is the deformable template based framework [1][2] 3] This approach of shape matching through global deformations is now well known and gives quite good results. A drawback of this technique is its computational cost. Such an approach could not be viable on a database of several thousands objects. While a final stage of deformable matching ....

R.C. Veltkamp and M. Hagedoorn. State of the art in shape matching. Technical Report UU-CS-1999-27, Utrecht, 1999.

....(sometimes classified as a statistical method) for classification [19] Fuzzy sets have also been used for shape classification [20] The above review is not a detailed review on shape silhouette classification approaches. For more detailed reviews on the topic, the reader is referred to [8][21][22] 3 The Proposed Approach Silhouette Representation: We represent the silhouette of an object by an ordered set of vectors V lV,V2, V) in the 2D Euclidian space, where L is the length of the object s silhouette. The external angle between any two successive vectors, Vi and Vi , is then ....

R. Veltkamp and M. Hagedoorn, "State-of-the-art in shape matching," Tech. Rep., Utrecht University, the Netherlands, 1999.

....Since these methods can be viewed as speeding up algorithms that can be described in more straightforward but less efficient terms, we do not focus on the details of these systems here. For a more detailed discussion of the variety of shape matching techniques, the reader is referred to [28]. 3. Introducing the Shape Context In order to compute shape correspondences and similarity, one must start by defining a shape descriptor. In analogy to the stereo matching problem, we would like to have descriptors that can be computed in one image and used to find corresponding points, if ....

R. C. Veltkamp and M. Hagedoorn. State of the art in shape matching. Technical Report UU-CS-1999-27, Utrecht, 1999.

....descriptors such as area or moments but such techniques often discard detailed shape information in the process. Shape similarity has also been studied in the psychology literature, an early example being Goldmeier [20] An extensive survey of shape matching in computer vision can be found in [58], 22] Broadly speaking, there are two approaches: 1) feature based, which involve the use of spatial arrangements of extracted features such as edge elements or junctions, and 2) brightness based, which make more direct use of pixel brightnesses. 2.1 Feature Based Methods A great deal of ....

R.C. Veltkamp and M. Hagedoorn, "State of the Art in Shape Matching," Technical Report UU-CS-1999-27, Utrecht, 1999.

....descriptors such as area or moments but such techniques often discard detailed shape information in the process. Shape similarity has also been studied in the psychology literature, an early example being Goldmeier [19] An extensive survey of shape matching in computer vision can be found in [57, 21]. Broadly speaking, there are two approaches: 1) feature based, which involve the use of spa tial arrangements of extracted features such as edge elements or junctions, and (2) brightness based, which make more direct use of pixel brightnesses. 2.1 Feature Based Methods A great deal of ....

R. C. Veltkamp and M. Hagedoorn. State of the art in shape matching. Technical Report UU-CS-1999-27, Utrecht, 1999.

....in a structure defined on a canonical parameterization, we can compare models by comparing their symmetry descriptors. This basis for comparison provides a means for shape registration, matching, and classification. In this respect, our goals are similar to previously described shape descriptors [17 20], of which some recent examples include spin images [21] harmonic shape images [22] shape contexts[23, 24] and Extended Gaussian Images [25] Similarly, our descriptor is related to several shape representations that characterize symmetries with respect to local axes, such as medial axes [26] ....

Veltkamp, R.C., Hagedoorn, M.: State-of-the-art in shape matching. Technical Report UUCS -1999-27, Utrecht University, the Netherlands (1999)

....In the context of image retrieval and shape similarity, several shape descriptors have been proposed, ranging from moments and Fourier descriptors to Hausdor distance and the medial axis transform. For an overview and a detailed discussion of shape matching techniques, the reader is referred to [9]. It should be emphasized that our approach is generically applicable as opposed to most shape matching techniques that are restricted to silhouettes and closed curves. In our framework shape refers to any type of boundary information, and in consequence, our algorithm is applicable for a large ....

R. C. Veltkamp and M. Hagedoorn. State of the art in shape matching. Technical Report UU-CS-1999-27, Utrecht, 1999.

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R. Veltkamp and M. Hagedoorn. State-of-the-art in Shape Matching. Technical Report UU-CS-1999.

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R. Veltkamp and M. Hagedoorn. State-of-the-art in Shape Matching. Technical Report UUCS -1999-27, Utrecht University, 1999. http://webdoc.gwdg.de/ebook/ah/2000/techrep/CS1997 /1997-27.pdf.

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Veltkamp, R.C., Hagedoorn, M.: State of the art in shape matching. In Lew, M.S., ed.: Principles of visual information retrieval. Springer-Verlag (2001) 87--119

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R. C. Veltkamp and M. Hagedoorn. State of the art in shape matching. Technical Report UU-CS-1999-27, Utrecht, 1999.

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R. Veltkamp and M. Hagedoorn. State-of-the-art in shape matching, Technical Report UU-CS-1999-27, Utrecht University, the Netherlands, 1999.

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Veltkamp, R., Hagedoorn, M., 1999. State-of-the-art in shape matching. Tech. Rep. UU-CS-1999-27, Utrecht University, the Netherlands.

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R. C. Veltkamp and M. Hagedoorn. State-of-the-art in shape matching. Technical Report UU-CS-1999-27, Utrecht University, the Netherlands, 1999.

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R. C. VeltKamp and M. Hagedoorn, "State-of-the-art in shape matching," in Principles of Visual Information Retrieval,M.S.Lew, Ed. Berlin, Germany: Springer-Verlag, 2001, Ser.: Advances in Pattern Recognition.

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R.C. Veltkamp and M. Hagedoorn, "State of the Art in Shape Matching," Technical Report UU-CS-1999-27, Utrecht, 1999.

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R. C. Veltkamp, M. Hagedoorn, State--of-- the--art in shape matching, in: Principles of Visual Information Retrieval, Springer, Heidelberg, 200, pp. 87--119.

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R. Veltkamp and M. Hagedoorn. State-of-the-art in shape matching, 1999.

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R. Veltkamp and M. Hagedoorn. State-of-the-art in Shape Matching. Technical Report UU-CS-1999-27, Utrecht University, Sept. 1999.

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R. Veltkamp and M. Hagedoorn. State-of-the-art in shape matching, Technical Report UU-CS-1999-27, Utrecht University, the Netherlands, 1999.

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