Fast Point-Feature Label Placement for Dynamic Visualizations (Thesis)

TL;DR

This paper introduces a real-time, scalable algorithm for automatic point-label placement on dynamic maps, enabling fast and conflict-free labeling without pre-processing, suitable for interactive visual analytics with large datasets.

Contribution

It presents a novel geometric de-confliction algorithm, the 'trellis strategy,' for real-time label placement on dynamic maps, overcoming NP-hard challenges without pre-processing.

Findings

Labels can be placed at multiple frames per second on maps with tens of thousands of nodes.

The trellis strategy effectively reduces label conflicts in dynamic visualizations.

The method scales well with dataset size and complexity.

Abstract

This paper describes a fast approach to automatic point label de-confliction on interactive maps. The general Map Labeling problem is NP-hard and has been the subject of much study for decades. Computerized maps have introduced interactive zooming and panning, which has intensified the problem. Providing dynamic labels for such maps typically requires a time-consuming pre-processing phase. In the realm of visual analytics, however, the labeling of interactive maps is further complicated by the use of massive datasets laid out in arbitrary configurations, thus rendering reliance on a pre-processing phase untenable. This paper offers a method for labeling point-features on dynamic maps in real time without pre-processing. The algorithm presented is efficient, scalable, and exceptionally fast; it can label interactive charts and diagrams at speeds of multiple frames per second on maps with tens of thousands of nodes. To accomplish this, the algorithm employs a novel geometric de-confliction approach, the 'trellis strategy,' along with a unique label candidate cost analysis to determine the "least expensive" label configuration. The speed and scalability of this approach make it well-suited for visual analytic applications.