Using camera state transforms for commuter network visualization

We present a novel approach for visualizing commuter networks, i.e., directed graphs whose nodes (cities and towns) each have a geographic location, and whose edges each have a direction and an associated number of commuters moving between two nodes. Our approach involves using camera state transforms that map the current camera state (position and orientation) to various rendering parameters to achieve a hybrid 2D-3D visualization. As the camera’s angle and distance change, the shapes and transparency levels of nodes and edges morph in response, allowing for a smooth transition between a 2D view (from above) to a 3D view (from the side) that reveals information in different ways.