Graph matching, which refers to a class of computational problems of finding an optimal
correspondence between the vertices of graphs to minimize (maximize) their node and edge …

The performance of matching and object recognition methods based on interest points
depends on both the properties of the underlying interest points and the choice of …

Not all interest points are equally interesting. The most valuable interest points lead to
optimal performance of the computer vision method in which they are employed. But a …

This paper presents a numerical study of the bottom-up and top-down inference processes
in hierarchical models using the And-Or graph as an example. Three inference processes …

To develop statistical methods for shapes with a tree-structure, we construct a shape space
framework for tree-shapes and study metrics on the shape space. This shape space has …

This work presents a theory and methodology for simultaneous detection of local spatial and
temporal scales in video data. The underlying idea is that if we process video data by spatio …

The bone graph (Macrini et al., in press, 2008)[23],[25] is a graph-based medial shape
abstraction that offers improved stability over shock graphs and other skeleton-based …

As an increasing number of digital images are generated, a demand for an efficient and
effective image retrieval mechanisms grows. In this work, we present a new skeleton-based …

Geometric trees can be formalized as unordered combinatorial trees whose edges are
endowed with geometric information. Examples are skeleta of shapes from images; …

Saliency computation has wide applications. It is now being used in almost all vision-related
applications. But, identifying saliency is still a problem. Various computational models have …