Dirk J. Lehmann

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Parallel coordinates and scatterplot matrices are widely used to visualize multi-dimensional data sets. But these visualization techniques are insufficient when the number of dimensions grows. To solve this problem, different approaches to pre-select the best views or dimensions have been proposed in the last years. However, there are still several(More)
Modern visualization methods are needed to cope with very high-dimensional data. Efficient visual analytical techniques are required to extract the information content in these data. The large number of possible projections for each method, which usually grow quadrat-ically or even exponentially with the number of dimensions, urges the necessity to employ(More)
The scatterplot matrix (SPLOM) is a well-established technique to visually explore high-dimensional data sets. It is characterized by the number of scatterplots (plots) of which it consists of. Unfortunately, this number quadrat-ically grows with the number of the data set's dimensions. Thus, a SPLOM scales very poorly. Consequently, the usefulness of(More)
The concept of continuous scatterplot (CSP) is a modern visualization technique. The idea is to define a scalar density value based on the map between an n-dimensional spatial domain and an m-dimensional data domain, which describe the CSP space. Usually the data domain is two-dimensional to visually convey the underlying, density coded, data. In this paper(More)
Erläuterungen anhand anschaulicher Beispiele verdeut-licht und so für den Leser nachvollziehbar. Abstract Concerning multi-dimensional data sets there exist a lot of visual-based as well as automatical techniques to detect inherent relations and characteristics. Due to the (increasing) size and complexity of such data, it is necessary to combine both(More)
Continuous Parallel Coordinates (CPC) are a contemporary visualization technique in order to combine several scalar fields, given over a common domain. They facilitate a continuous view for parallel coordinates by considering a smooth scalar field instead of a finite number of straight lines. We show that there are feature curves in CPC which appear to be(More)
Two-dimensional transfer functions are an effective and well-accepted tool in volume classification. The design of them mostly depends on the user's experience and thus remains a challenge. Therefore, we present an approach in this paper to automate the transfer function design based on 2D density plots. By exploiting their smoothness, we adopted the Morse(More)
Cerebral aneurysms are a pathological vessel dilatation that bear a high risk of rupture. For the understanding and evaluation of the risk of rupture, the analysis of hemodynamic information plays an important role. Besides quantitative hemodynamic information, also qualitative flow characteristics, e.g., the inflow jet and impingement zone are correlated(More)