Multidimensional Projection Visualization: Control-points Selection and Inverse Projection Exploration
Abstract
The task of interpreting multidimensional data is as important as it is challenging. The importance comes from the fact that virtually every data worth analyzing is multidimensional, while the challenge comes from the very nature of these data sets, as the multiple features describing each instance can quickly overwhelm our visual perception system, thus making it difficult to observe meaningful information. Visualization techniques play an essential role in simplifying this task, by preprocessing the data to extract critical features and displaying them effectively, by using visual metaphors that can be easily understood. Multidimensional Projection (MP) is one of such techniques, whose fundamental goal is to present an overview of the data distribution in the form of a 2D scatterplot graph. It does so by reducing the dimensionality of the dataset in such a way that distances are preserved as much as possible. MP approaches, along with most visualizations, are shifting from a static display to a more interactive one, allowing human intervention to modify the layout and facilitate exploration and understanding of the data. In this thesis, I present contributions that specifically relate to interactive aspects of multidimensional projection. First, I propose a computational framework and methodology for control points selection. Control points are a particular set of projected points used to steer and rearrange the projection layout. I demonstrate the proposed method can improve the projection quality while requiring only a small amount of control points. Second, I introduce inverse projection, a novel paradigm to create multidimensional points exclusively through 2D interactions. The projection space is transformed into a canvas, where new points can be added. These new points are then mapped into the original multidimensional space, i.e., they become unique multidimensional instances themselves. Lastly, I present the usability of the inverse projection framework in two demonstration examples. (1) A parameter exploration prototype system for optimization with multiple minima. (2) A face-synthesis application, where new face models are generated on the fly.
Description
Keywords
Computer Science
Citation
Portes dos Santos Amorim, E. (2016). Multidimensional Projection Visualization: Control-points Selection and Inverse Projection Exploration (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/27026