A dynamic system for object description and correspondence

Parvin, Bahram; Medioni, Gérard

doi:10.1109/cvpr.1991.139722

Cited by 10 publications

(10 citation statements)

References 20 publications

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“…The graph recovered at this step is similar to graphs suggested by other researchers (e.g. 8,18,11]). This graph is a surface based description and not a volumetric description.…”

Section: From Image To Segmented Surface Descriptionsupporting

confidence: 83%

Part decomposition and description of 3D shapes

Rom

Medioni²

Proceedings of 12th International Conference on Pattern Recognition

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We address the problem of obtaining natural (intuitive) descriptions of 3D shapes. We present o n e o f the rst attempts to address the description of 3D compound objects, where the parts are connected smoothly. The input we consider is either complete 3D data or range data from a single view. We suggest a volumetric graph representation of the object, where the nodes represent individual parts and the edges represent connectivity information. We suggest the use of properties of the parabolic curves for performing the part decomposition. We currently consider parts with tubular structure with a straight or curved axis. The graph description presents a structural description of the shape in terms of parts and their arrangement. We are also interested in the internal description of the parts. We study two well de ned classes of shapes, namely Straight Homogeneous Generalized Cylinders, and Planar Right Constant GCs. We suggest the use of properties of the parabolic curves for recovering natural descriptions of these classes in terms of their cross sections and axes.

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“…The graph recovered at this step is similar to graphs suggested by other researchers (e.g. 8,18,11]). This graph is a surface based description and not a volumetric description.…”

Section: From Image To Segmented Surface Descriptionsupporting

confidence: 83%

Part decomposition and description of 3D shapes

Rom

Medioni²

Proceedings of 12th International Conference on Pattern Recognition

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“…Which subgraphs of the scene are isomorphic to which subgraphs in the models? In computer vision, graph matching is widely used (see, e.g., Fan, 1990;Lowe, 1987;Nevatia and Price 1992;Parvin and Medioni, 1991). In the worst case, the subgraph isomorphism problem is NP-complete.…”

Section: Representation and Matchingmentioning

confidence: 99%

Perceptual grouping for generic recognition

Havaldar

Medioni

Stein

1996

Int J Comput Vision

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We address the problem of recognition of generic objects from a single intensity image. This precludes the use of purely geometric methods which assume that models are geometrically and precisely designed. Instead, we propose to use descriptions in terms of features and their qualitative geometric relationships. To succeed, it is clear that these features need to be high level, rather than points or lines. We propose to detect groups using perceptual organization criteria such as proximity, symmetry, parallelism, and closure. The detection of these features is performed in an efficient way using proximity indexing. Since many groups are created, we also perform selection of relevant groups by organizing them into sets of similar perceptual content. Finally we present an implementation of a recognition system using these sets as primitives. It is an efficient colored graph matching algorithm using the adjacency matrix representation of a graph. Using indexing, we retrieve matching hypotheses, which are verified against each other with respect to topological constraints. Groups of consistent hypotheses represent detected model instances in a scene. The complete system is illustrated on real images. We also discuss further extensions.

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“…Our work for 3D boundary completion is conceptually unique since it is based on weak smoothness constraints and geomeixic cohesion (Parvin and Medioni, 1991b). The weak smoothness constraint implies that joining of two curve segments shouldbe smooth, unless they intersect to form a vertex.…”

Section: Grouping Of 3-d Segmentsmentioning

confidence: 99%

“…We aim to represent each curve segment with the minimum number of piecewise continuous polynomials. This is a two step process, where a curve segment is initially partitioned with a polygon fit, then the partition is refined by localization of corners (see Saint-Marc et al, 1991;Parvin, 1991) for more details on corner extraction). This step results in identification of vertices and representation of data points between these vertices by B-spline segments.…”

Section: Long Term Variablesmentioning

confidence: 99%

“…Finally, in Section 4, we explain how the results of the correspondence problem can be used for B-rep reconstruction. We should also add that some of the images, used in this paper, were generated at USC (Fan et al, 1989;Parvin, 1991) using the Technical Art range finder, and the rest were obtained from Michigan State University (Flynn and Jain, 1991).…”

Section: Introductionmentioning

confidence: 99%

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B-rep object description from multiple range views

Parvin

Medioni

1996

Int J Comput Vision

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We present a system which computes an integrated description of an object from multiple range images. The object description is in the form of B-rep (boundary representation), which has not been achieved by the computer vision community. To do so, we emphasize the inherent difficulties and ambiguities in the low to mid level vision, and present novel techniques of resolving them. In this system, each view of the object is represented as an attributed graph, where nodes correspond to the surfaces (vertices) and links represent the relationship between surfaces. The main issue in surface extraction is contour closure, which is formulated as a dynamic network. The underlying principle for this network is weak smoothness and geometric cohesion, and is modeled as the interaction between long and short term variables. Long term variables represent the initial boundary grouping computed from the low level surface features, and short term variables represent the competing hypotheses that cooperate with the long term variables.The matching problem involves matching visible surfaces and vertices, and provides the necessary basis for volumetric reconstruction from multiple views. The matching strategy is a two step process, where in each step uses the Hopfield network. At each step, we specify a set of local, adjacency and global constraints, and define an appropriate energy function to be minimized. At the first level of this hierarchy, surface patches are matched and the rigidity transformation is computed. At the second level, the mapping is refined by matching the corresponding vertices, and the transformation is verified.The multiple-view reconstruction consists of two steps. First, we build a composite graph that contains the bounding surfaces and their corresponding attributes, and then intersect these surfaces so that the edges and vertices corresponding to the B-rep description are identified. We present results on objects with planar, as well as quadratically-curved, surfaces.

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A dynamic system for object description and correspondence

Cited by 10 publications

References 20 publications

Part decomposition and description of 3D shapes

Part decomposition and description of 3D shapes

Perceptual grouping for generic recognition

B-rep object description from multiple range views

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