This paper proposes an advanced cut-and-paste editing for three-dimensional models. We introduce a new parameterization technique based on constrained B-spline surface/volume fitt...
Yoshiyuki Furukawa, Hiroshi Masuda, Kenjiro T. Miu...
We present a new Bayesian approach to object identification: variants. By object identification we mean the detection of the member (regular variant) of a given statistical popula...
In this paper, we propose a competitive image segmentation algorithm. It is a dynamic evolving optimization method, which we call the population algorithm. The method is inspired f...
Cor J. Veenman, Marcel J. T. Reinders, Eric Backer
In this paper, we study the problem of scheduling parallel loops at compile-time for a heterogeneous network of machines. We consider heterogeneity in three aspects of parallel pr...
The paper introduces a framework for clustering data objects in a similarity-based context. The aim is to cluster objects into a given number of classes without imposing a hard pa...