We present a novel approach to segmenting video using iterated graph cuts based on spatio-temporal volumes. We use the mean shift clustering algorithm to build the spatio-temporal volumes with different bandwidths from the input video. We compute the prior probability obtained by the likelihood from a color histogram and a distance transform using the segmentation results from graph cuts in the...

This paper presents an iterated region merging-based graph cuts algorithm which is a novel extension of the standard graph cuts algorithm. Graph cuts addresses segmentation in an optimization framework and finds a globally optimal solution to a wide class of energy functions. However, the extraction of objects in a complex background often requires a lot of user interaction. The proposed algori...

Previous work has demonstrated a straightforward mapping from Conceptual Graphs (CGs) to Formal Concept Analysis (FCA), and the combined benefits these types of Conceptual Structures bring in capturing and reasoning about the semantics in system design. As in that work, a CGs Transaction Model (or `Transaction Graph’) exemplar is used, but in the form of a richer Financial Trading (FT) case stu...

We investigate the usage of Ant Colony Optimization to detect balanced graph cuts. In order to do so we develop an algorithm based on competing ant colonies. We use a heuristic from social network analysis called the edge clustering coefficient, which greatly helps our colonies in local search. The algorithm is able to detect cuts that correspond very well to known cuts on small real-world netw...

Convexity is a notion that has been defined for subsets of R and for subsets of general graphs. A convex cut of a graph G = (V,E) is a 2-partition V1∪̇V2 = V such that both V1 and V2 are convex, i. e., shortest paths between vertices in Vi never leave Vi, i ∈ {1, 2}. Finding convex cuts is NP-hard for general graphs. To characterize convex cuts, we employ the Djoković relation, a reflexive and s...