Consistent labeling of rotating maps

Dynamic maps that allow continuous map rotations, for example, on mobile devices, encounter new geometric labeling issues unseen in static maps before. We study the following dynamic map labeling problem: The input is an abstract map consisting of a set P of points in the plane with attached horizontally aligned rectangular labels. While the map with the point set P is rotated, all labels remain horizontally aligned. We are interested in a consistent labeling of P under rotation, i.e., an assignment of a single (possibly empty) active interval of angles for each label that determines its visibility under rotations such that visible labels neither intersect each other (soft conflicts) nor occlude points in P at any rotation angle (hard conflicts). Our goal is to find a consistent labeling that maximizes the number of visible labels integrated over all rotation angles. We first introduce a general model for labeling rotating maps and derive basic geometric properties of consistent solutions. We show NP-hardness of the above optimization problem even for unit-square labels. We then present a constant-factor approximation for this problem based on line stabbing, and refine it further into an efficient polynomial-time approximation scheme (EPTAS)

A Framework for Algorithm Stability

We say that an algorithm is stable if small changes in the input result in small changes in the output. This kind of algorithm stability is particularly relevant when analyzing and visualizing time-varying data. Stability in general plays an important role in a wide variety of areas, such as numerical analysis, machine learning, and topology, but is poorly understood in the context of (combinatorial) algorithms. In this paper we present a framework for analyzing the stability of algorithms. We focus in particular on the tradeoff between the stability of an algorithm and the quality of the solution it computes. Our framework allows for three types of stability analysis with increasing degrees of complexity: event stability, topological stability, and Lipschitz stability. We demonstrate the use of our stability framework by applying it to kinetic Euclidean minimum spanning trees

Trajectory-Based Dynamic Map Labeling

In this paper we introduce trajectory-based labeling, a new variant of dynamic map labeling, where a movement trajectory for the map viewport is given. We define a general labeling model and study the active range maximization problem in this model. The problem is NP-complete and W[1]-hard. In the restricted, yet practically relevant case that no more than k labels can be active at any time, we give polynomial-time algorithms. For the general case we present a practical ILP formulation with an experimental evaluation as well as approximation algorithms.Comment: 19 pages, 7 figures, extended version of a paper to appear at ISAAC 201

Evaluation of Labeling Strategies for Rotating Maps

We consider the following problem of labeling points in a dynamic map that allows rotation. We are given a set of points in the plane labeled by a set of mutually disjoint labels, where each label is an axis-aligned rectangle attached with one corner to its respective point. We require that each label remains horizontally aligned during the map rotation and our goal is to find a set of mutually non-overlapping active labels for every rotation angle $\alpha \in [0, 2\pi)$ so that the number of active labels over a full map rotation of 2$\pi$ is maximized. We discuss and experimentally evaluate several labeling models that define additional consistency constraints on label activities in order to reduce flickering effects during monotone map rotation. We introduce three heuristic algorithms and compare them experimentally to an existing approximation algorithm and exact solutions obtained from an integer linear program. Our results show that on the one hand low flickering can be achieved at the expense of only a small reduction in the objective value, and that on the other hand the proposed heuristics achieve a high labeling quality significantly faster than the other methods.Comment: 16 pages, extended version of a SEA 2014 pape

Visualization Algorithms for Maps and Diagrams

One of the most common visualization tools used by mankind are maps or diagrams. In this thesis we explore new algorithms for visualizing maps (road and argument maps). A map without any textual information or pictograms is often without use so we research also further into the field of labeling maps. In particular we consider the new challenges posed by interactive maps offered by mobile devices. We discuss new algorithmic approaches and experimentally evaluate them

Consistent labeling of rotating maps

Dynamic maps that allow continuous map rotations, for example, on mobile devices, encounter new geometric labeling issues unseen in static maps before. We study the following dynamic map labeling problem: The input is an abstract map consisting of a set $P$ of points in the plane with attached horizontally aligned rectangular labels. While the map with the point set $P$ is rotated, all labels remain horizontally aligned. We are interested in a consistent labeling of $P$ under rotation, i.e., an assignment of a single (possibly empty) active interval of angles for each label that determines its visibility under rotations such that visible labels neither intersect each other (soft conflicts) nor occlude points in $P$ at any rotation angle (hard conflicts). Our goal is to find a consistent labeling that maximizes the number of visible labels integrated over all rotation angles.We first introduce a general model for labeling rotating maps and derive basic geometric properties of consistent solutions. We show NP-hardness of the above optimization problem even for unit-square labels. We then present a constant-factor approximation for this problem based on line stabbing, and refine it further into an efficient polynomial-time approximation scheme (EPTAS)