The integral image representation is a remarkable idea that permits to evaluate the sum of image values over rectangular regions of the image with four operations, regardless of the size of the region. It was first proposed under the name of summed area table in the computer graphics community by Crow’84, in order to efficiently filter texture maps. It was later popularized in the computer visi...

In deep neural network model training and prediction, due to the limitation of GPU memory computing resources, massive image data must be cropped into limited-sized samples. Moreover, in order improve generalization ability model, samples need randomly distributed experimental area. Thus, background information is often incomplete or even missing. On this condition, a knowledge graph applied se...

Error-tolerant graph matching gathers an important family of problems. These problems aim at finding correspondences between two graphs while integrating error model. In the Graph Edit Distance (GED) problem, insertion/deletion edges/nodes from one to another is explicitly expressed by At opposite, problem commonly referred as “graph matching” does not express such operations. For decades, thes...

This paper formulates a necessary and sufficient condition for a generic graph matching problem to be equivalent to the maximum vertex and edge weight clique problem in a derived association graph. The consequences of this results are threefold: first, the condition is general enough to cover a broad range of practical graph matching problems; second, a proof to establish equivalence between gr...

Many applications such as information retrieval and classification, involve measuring graph distance or similarity, i.e., matching graphs to identify and quantify their common features. Different kinds of graph matchings have been proposed, giving rise to different graph similarity or distance measures. Graph matchings may be univalent – when each vertex is associated with at most one vertex of...

This paper formulates a necessary and sufficient condition for a generic graph matching problem to be equivalent to the maximum vertex and edge weight clique problem in a derived association graph. The consequences of this results are threefold: first, the condition is general enough to cover a broad range of practical graph matching problems; second, a proof to establish equivalence between gr...

Graph matching is an important problem in machine learning and pattern recognition. Herein, we present theoretical and practical results on the consistency of graph matching for estimating a latent alignment function between the vertex sets of two graphs, as well as subsequent algorithmic implications when the latent alignment is partially observed. In the correlated Erdős-Rényi graph setting, ...

This paper first reviews some theoretical results in errortolerant graph matching that were obtained recently. The results include a new metric for error-tolerant graph matching based on maximum common subgraph, a relation between maximum common subgraph and graph edit distance, and the existence of classes of cost functions for error-tolerant graph matching. Then some new optimal algorithms fo...

Abstract: The aim of this paper is to develop a new approach for a solution of the continuous-time model matching problem with a static state feedback in the sense of H∞ optimality criterion. The main contribution is to reformulate the H∞ model matching problem in linear matrix inequality settings, to present the solvability conditions and to give a design procedure for a one degree of freedom ...