Background: Modeling of gene expression data from time course experiments often involves the use of linear models such as those obtained from principal component analysis (PCA), i...
Peter D. Wentzell, Tobias K. Karakach, Sushmita Ro...
This paper proposes a novel volume-based motion capture method using a bottom-up analysis of volume data and an example topology database of the human body. By using a two-step gra...
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
Objective: Currently, visualization support for patient data analysis is mostly limited to the representation of directly measured data. Contextual information on performed treatm...
—The distance transform has found many applications in image analysis. Chamfer distance transforms are a class of discrete algorithms that offer a good approximation to the desir...