NDLI: Temporal map labeling: a new unified framework with experiments

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Temporal map labeling: a new unified framework with experiments

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Temporal map labeling: a new unified framework with experiments

Content Provider	ACM Digital Library
Author	Niedermann, Benjamin Nöllenburg, Martin Barth, Lukas Strash, Darren
Abstract	The increased availability of interactive maps on the Internet and on personal mobile devices has created new challenges in computational cartography and, in particular, for label placement in maps. Operations like rotation, zoom, and translation dynamically change the map over time and make a consistent adaptation of the map labeling necessary. In this paper, we consider map labeling for the case that a map undergoes a sequence of operations over a specified time span. We unify and generalize several preceding models for dynamic map labeling into one versatile and flexible model. In contrast to previous research, we completely abstract from the particular operations (e.g., zoom, rotation, etc.) and express the labeling problem as a set of time intervals representing the labels' presences, activities, and conflicts. The model's strength is manifested in its simplicity and broad range of applications. In particular, it supports label selection both for map features with fixed position as well as for moving entities (e.g., for tracking vehicles in logistics or air traffic control). Through extensive experiments on OpenStreetMap data, we evaluate our model using algorithms of varying complexity as a case study for navigation systems. Our experiments show that even simple (and thus, fast) algorithms achieve near-optimal solutions in our model with respect to an intuitive objective function.
Starting Page	1
Ending Page	10
Page Count	10
File Format	PDF
ISBN	9781450345897
DOI	10.1145/2996913.2996957
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-10-31
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Dynamic maps Unified labeling models Label selection
Content Type	Text
Resource Type	Article

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