While there is a very long tradition of approximating a data array by projecting row or column vectors into a lower dimensional subspace the direct approximation of a data matrix ...
Numerical particle simulations and astronomical observations create huge data sets containing uncorrelated 3D points of varying size. These data sets cannot be visualized interact...
Abstract. Recently, we have proposed a novel method for the compression of time series based on mathematical models that explore dependencies between different time series. This r...
High compression of plant geometry is an important aspect in fast realistic visualization of plants. Hierarchical structuring plant morphology is a key factor for real time plant r...
We present a fast method that adaptively approximates large-scale functional scattered data sets with hierarchical B-splines. The scheme is memory efficient, easy to implement an...