Interactive visualization of streaming data with Kernel Density Estimation

Lampe, Ove Daae; Hauser, Helwig

doi:10.1109/pacificvis.2011.5742387

Cited by 93 publications

(22 citation statements)

References 22 publications

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“…The main bottleneck is density estimation which can be addressed by parallelizing the respective computation as mentioned before. However, in the future we also want to investigate a GPU implementation of the kernel density estimation [3,30] as well as of Marching Cubes. This would also address the second performance bottleneck of CloudLasso and take advantage of the fact that the data from the density estimation would already be available in GPU memory.…”

Section: Limitationsmentioning

confidence: 99%

Efficient Structure-Aware Selection Techniques for 3D Point Cloud Visualizations with 2DOF Input

Efstathiou

Isenberg

et al. 2012

IEEE Trans. Visual. Comput. Graphics

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Abstract-Data selection is a fundamental task in visualization because it serves as a pre-requisite to many follow-up interactions. Efficient spatial selection in 3D point cloud datasets consisting of thousands or millions of particles can be particularly challenging. We present two new techniques, TeddySelection and CloudLasso, that support the selection of subsets in large particle 3D datasets in an interactive and visually intuitive manner. Specifically, we describe how to spatially select a subset of a 3D particle cloud by simply encircling the target particles on screen using either the mouse or direct-touch input. Based on the drawn lasso, our techniques automatically determine a bounding selection surface around the encircled particles based on their density. This kind of selection technique can be applied to particle datasets in several application domains. TeddySelection and CloudLasso reduce, and in some cases even eliminate, the need for complex multi-step selection processes involving Boolean operations. This was confirmed in a formal, controlled user study in which we compared the more flexible CloudLasso technique to the standard cylinder-based selection technique. This study showed that the former is consistently more efficient than the latter-in several cases the CloudLasso selection time was half that of the corresponding cylinder-based selection.

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Section: Limitationsmentioning

confidence: 99%

Efficient Structure-Aware Selection Techniques for 3D Point Cloud Visualizations with 2DOF Input

Efstathiou

Isenberg

et al. 2012

IEEE Trans. Visual. Comput. Graphics

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“…Specifically, active parts can be shown in full detail while inactive can be aggregated, for example, in a density surface [39,53]. Examples of using these approaches can be seen in Sect.…”

Section: Filteringmentioning

confidence: 99%

Clustering Trajectories by Relevant Parts for Air Traffic Analysis

Andrienko

Fuchs

et al. 2018

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. Different approach routes to London airports are represented in a 3D view by central trajectories of density-based clusters of relevant parts of flight trajectories. The images show the routes that were used in two days with different wind parameters.Abstract-Clustering of trajectories of moving objects by similarity is an important technique in movement analysis. Existing distance functions assess the similarity between trajectories based on properties of the trajectory points or segments. The properties may include the spatial positions, times, and thematic attributes. There may be a need to focus the analysis on certain parts of trajectories, i.e., points and segments that have particular properties. According to the analysis focus, the analyst may need to cluster trajectories by similarity of their relevant parts only. Throughout the analysis process, the focus may change, and different parts of trajectories may become relevant. We propose an analytical workflow in which interactive filtering tools are used to attach relevance flags to elements of trajectories, clustering is done using a distance function that ignores irrelevant elements, and the resulting clusters are summarized for further analysis. We demonstrate how this workflow can be useful for different analysis tasks in three case studies with real data from the domain of air traffic. We propose a suite of generic techniques and visualization guidelines to support movement data analysis by means of relevance-aware trajectory clustering.

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“…Density maps have been used for revealing concentrations of flows at the cost of loss of detail concerning the links themselves (Nielsen and Hovgesen 2008;Rae 2009Rae , 2011Lampe and Hauser 2011). Combinations of choropleth maps, point and linear symbols, and custom made glyphs are used by Specht and Hanewinkel (2011) to analyse commuting patterns in Germany.…”

Section: Related Workmentioning

confidence: 99%

An Interactive Approach for Exploration of Flows Through Direction-Based Filtering

2017

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This paper is concerned with the representation and exploration of flows, defined as spatial interactions between geographic locations. Flows are challenging to display in a comprehensible manner due to the nature of the data, which are characterized by many crossings and overlaps leading to clutter. A number of different strategies have been suggested for addressing this problem, which commonly involve reducing the search space, aggregating the data or simplifying the representations often at the cost of information loss or distortion of spatial context. We propose an interactive approach for exploring large and highly connected networks of flows without distorting the geographical space and without losing the context overview in the process. The approach is based on a flow-specific interaction technique for filtering the data by direction, City University London, London EC1V OHB, UK that enables an analyst to successively identify underlying spatial arrangement patterns. We illustrate our approach through exploring flows of tourists and locals in the Greater London area.

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Interactive visualization of streaming data with Kernel Density Estimation

Cited by 93 publications

References 22 publications

Efficient Structure-Aware Selection Techniques for 3D Point Cloud Visualizations with 2DOF Input

Efficient Structure-Aware Selection Techniques for 3D Point Cloud Visualizations with 2DOF Input

Clustering Trajectories by Relevant Parts for Air Traffic Analysis

An Interactive Approach for Exploration of Flows Through Direction-Based Filtering

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