Function-described graphs for modelling objects represented by sets of attributed graphs

Serratosa, Francesc; Alquézar, René; Sanfeliu, Alberto

doi:10.1016/s0031-3203(02)00107-3

Cited by 61 publications

(58 citation statements)

References 21 publications

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“…Examples of the last one can be found in (Campbell & Flynn, 1999) of in (Skocaj & Leonardis, 2001). Another view-based object recognition strategy is described in (Serratosa et al, 2003). They use a Function-Described Graph (FDG) that gives a compact representation of a set of attributed graphs corresponding to several views of polyhedral objects.…”

Section: State Of the Art In 3d Recognition Methodsmentioning

confidence: 99%

Experiences in Recognizing Free-Shaped Objects from Partial Views by Using Weighted Cone Curvatures

Cerrada¹,

Salamanca²,

Adán³

et al. 2011

Object Recognition

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Section: State Of the Art In 3d Recognition Methodsmentioning

confidence: 99%

Experiences in Recognizing Free-Shaped Objects from Partial Views by Using Weighted Cone Curvatures

Cerrada¹,

Salamanca²,

Adán³

et al. 2011

Object Recognition

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“…Wong and You [27] proposed the First-Order Random Graphs (FORGS) with strong simplifications of the GRG, specifically they introduce three assumptions about the probabilistic independence between vertices and arcs which restrict too much the applicability of these graphs to object recognition. Later, our group introduced a new class of graphs called Function-Described Graphs (FDG) [20] to overcome some of the problems of the FORG. The FDG also considers some independence assumptions, but some useful 2 º order functions are included to constrain the generalisation of the structure.…”

Section: Matching Views Of 2d Projections Of 3d Objects By Random Graphsmentioning

confidence: 99%

The Use of Graph Techniques for Identifying Objects and Scenes in Indoor Building Environments for Mobile Robots

Sanfeliu

2004

Lecture Notes in Computer Science

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Abstract. In this paper we present some of the common issues that appear when we try to recognize objects in indoor scenes of a building, and we describe some strategies for recognizing them by using graph techniques. These scene images are captured by the colour cameras of a mobile robot, which in the learning phase, learn the objects by taken a set of 2D images of the projective object views. Then afterwards, the robot must identify the objects once its moves through the area that has been used to learn the objects. We describe two strategies to use graph techniques for object and scene recognition, some algorithms and preliminary results.

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“…Random Graphs such as FirstOrder Random Graphs (FORGs) [20], Function-Described Graphs (FDGs) [17,18] and Second-Order Random Graphs (SORGs) [16]; a Maximally General Prototype [4]; the Median Graph [9] and the Barycenter Graph [8] have been proposed as representatives of a set of graphs, among others. Most of these methods suffer from a prohibitive computation time or are limited to a restricted family of graphs.…”

Section: Introductionmentioning

confidence: 99%

A Comparison between Two Representatives of a Set of Graphs: Median vs. Barycenter Graph

Bardají

Ferrer

Sanfeliu

2010

Lecture Notes in Computer Science

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Abstract. In this paper we consider two existing methods to generate a representative of a given set of graphs, that satisfy the following two conditions. On the one hand, that they are applicable to graphs with any kind of labels in nodes and edges and on the other hand, that they can handle relatively large amount of data. Namely, the approximated algorithms to compute the Median Graph via graph embedding and a new method to compute the Barycenter Graph. Our contribution is to give a new algorithm for the barycenter computation and to compare it to the median Graph. To compare these two representatives, we take into account algorithmic considerations and experimental results on the quality of the representative and its robustness, on several datasets.

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Function-described graphs for modelling objects represented by sets of attributed graphs

Cited by 61 publications

References 21 publications

Experiences in Recognizing Free-Shaped Objects from Partial Views by Using Weighted Cone Curvatures

Experiences in Recognizing Free-Shaped Objects from Partial Views by Using Weighted Cone Curvatures

The Use of Graph Techniques for Identifying Objects and Scenes in Indoor Building Environments for Mobile Robots

A Comparison between Two Representatives of a Set of Graphs: Median vs. Barycenter Graph

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