Relational graphs are a fundamental type of scene representation for medium and high level computer vision tasks. They provide a generic way of encoding entities and relationships. The comparison and matching of such graphs is an important and challenging problem under the conditions of uncertainty and corruption which exist in most vision problems. In this thesis a method for matching relation...

  The clustering problem under the criterion of minimum sum of squares is a non-convex and non-linear program, which possesses many locally optimal values, resulting that its solution often falls into these trap and therefore cannot converge to global optima solution. In this paper, an efficient hybrid optimization algorithm is developed for solving this problem, called Tabu-KM. It gathers the ...

The clustering problem under the criterion of minimum sum square of errors is a non-convex and non-linear problem, which possesses many locally optimal values, resulting that its solution often being stuck at locally optimal solution. In this paper, a hybrid genetic, tabu search and k-means algorithm, called GeneticTKM, is proposed for the clustering problem. A new mutation operator is presente...

We offer an equilibrium characterization of a general class of global games with strategic complementarities. The analysis highlights a form of acyclicity in the interim belief structure of global games, which allows us to formalize a selection criterion, iterated generalized half-dominance. This criterion is shown to be a unique global game selection when noise distributions satisfy a regulari...

This paper presents an improved segmentation approach derived from mean shift for natural images. The optimal color bandwidth under Plug-in rule is not always satisfying in the actual vision tasks, and a changing color bandwidth is helpful for controlling the segmentation result. The performance of direct density searching is better than mean shift under the same spatial bandwidth. A global opt...

A novel frequency and modal domain formulation of the model updating problem is presented. Deviations in discrete frequency responses and eigenfrequencies, between the model to be updated and a reference model, constitute the criterion function. A successful updating thus results in a model with the reference’s input-output relations at selected frequencies. The formulation is demonstrated to p...

Pearl’s well-known d-separation criterion for an acylic directed graph (ADG) is a pathwise separation criterion that can be used to efficiently identify all valid conditional independence relations in the Markov model determined by the graph. This paper introduces p-separation, a pathwise separation criterion that efficiently identifies all valid conditional independences under the Andersson-Ma...

An hybrid segmentation method for color images is presented in this work. It combines 2D histogram clustering to produce segmentation maps fused together providing an initial unsupervised clustering of the dominant colors of the image. Region information is then used and a novel technique is introduced to simplify the Region Adjacency Graph by merging candidate regions until the stabilization o...