论文标题

无Zoomless Maps:以固定地图比例尺的互动探索互动探索的外部标签方法

Zoomless Maps: External Labeling Methods for the Interactive Exploration of Dense Point Sets at a Fixed Map Scale

论文作者

Gedicke, Sven, Bonerath, Annika, Niedermann, Benjamin, Haunert, Jan-Henrik

论文摘要

在智能手机和智能手表等小屏幕设备上可视化空间数据在计算制图中带来了新的挑战。当前的地图探索接口要求其用户经常放大和缩小。实际上,缩放和平移是适合选择与感兴趣区域相对应的地图范围的工具。但是,它们并不适合解决由高特征密度引起的图形混乱,因为放大大图刻度会导致上下文丧失。因此,我们提出了新的外部标签方法,这些方法允许通过密集的兴趣点导航,同时保持当前地图范围固定。我们提供了一个统一的模型,其中标签位于地图的边界上,并通过连接线与相应的特征在视觉上相关联,这称为领导者。由于屏幕空间有限,因此同时标记所有功能是不切实际的。因此,在任何时候,我们都会标记一个特征的子集。我们提供的交互技术可以系统地更改当前功能的选择,从而使用户访问所有功能。我们区分了三种方法,这些方法允许用户沿着地图的底部滑动标签,或者根据页面或堆栈浏览标签。我们提出了一种通用算法框架,该框架为我们提供了以统一的方式表达相互作用技术的不同变体作为优化问题的可能性。我们提出了确切的算法和快速,简单的启发式方法,这些算法考虑了不同的标准,例如标签的排名,总领导者长度和领导者之间的距离。我们通过实验评估了这些算法,并讨论了它们的优势和劣势,证明了所提出的算法框架的灵活性。

Visualizing spatial data on small-screen devices such as smartphones and smartwatches poses new challenges in computational cartography. The current interfaces for map exploration require their users to zoom in and out frequently. Indeed, zooming and panning are tools suitable for choosing the map extent corresponding to an area of interest. They are not as suitable, however, for resolving the graphical clutter caused by a high feature density since zooming in to a large map scale leads to a loss of context. Therefore we present new external labeling methods that allow navigating through dense sets of points of interest while keeping the current map extent fixed. We provide a unified model, in which labels are placed at the boundary of the map and visually associated with the corresponding features via connecting lines, which are called leaders. Since the screen space is limited, labeling all features at the same time is impractical. Therefore, at any time, we label a subset of the features. We offer interaction techniques to change the current selection of features systematically and, thus, give the user access to all features. We distinguish three methods, which allow the user either to slide the labels along the bottom side of the map or to browse the labels based on pages or stacks. We present a generic algorithmic framework that provides us with the possibility of expressing the different variants of interaction techniques as optimization problems in a unified way. We propose both exact algorithms and fast and simple heuristics that solve the optimization problems taking into account different criteria such as the ranking of the labels, the total leader length and the distance between leaders. We experimentally evaluate these algorithms and discuss the three variants with respect to their strengths and weaknesses proving the flexibility of the presented algorithmic framework.

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