TY  - JOUR
AU  - Miquel Ferrer
AU  - Dimosthenis Karatzas
AU  - Ernest Valveny
AU  - I. Bardaji
AU  - Horst Bunke
PY  - 2011//
TI  - A Generic Framework for Median Graph Computation based on a Recursive Embedding Approach
T2  - CVIU
JO  - Computer Vision and Image Understanding
SP  - 919
EP  - 928
VL  - 115
IS  - 7
KW  - Median Graph
KW  - Graph Embedding
KW  - Graph Matching
KW  - Structural Pattern Recognition
N2  - The median graph has been shown to be a good choice to obtain a represen- tative of a set of graphs. However, its computation is a complex problem. Recently, graph embedding into vector spaces has been proposed to obtain approximations of the median graph. The problem with such an approach is how to go from a point in the vector space back to a graph in the graph space. The main contribution of this paper is the generalization of this previ- ous method, proposing a generic recursive procedure that permits to recover the graph corresponding to a point in the vector space, introducing only the amount of approximation inherent to the use of graph matching algorithms. In order to evaluate the proposed method, we compare it with the set me- dian and with the other state-of-the-art embedding-based methods for the median graph computation. The experiments are carried out using four dif- ferent databases (one semi-artificial and three containing real-world data). Results show that with the proposed approach we can obtain better medi- ans, in terms of the sum of distances to the training graphs, than with the previous existing methods.
N1  - DAG
ID  - Miquel Ferrer2011
ER  -