Visualization of a multidimensional point cloud as a 3D swarm of avatars

The article presents an innovative approach to the visualization of multidimensional data, using icons inspired by Chernoff faces. The approach merges classical projection techniques with the assignment of particular data dimensions to mimic features, capitalizing on the natural ability of the human brain to interpret facial expressions. We introduce a semantic division of data dimensions into intuitive and technical categories, assigning the former to avatar features and projecting the latter into a hyperspace of four, or potentially more dimensions. The technique is implemented as a plugin to the dpVision open-source image handling platform. The plugin allows the data to be interactively explored in the form of a swarm of avatars whose position in hyperspace as well as facial features represent various aspects of the data. Sample visualizations, based on synthetic test data as well as the 12-dimensional database on Portuguese Vinho Verde wines, confirm the usefulness of our approach to the analysis of complex data structures.