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Memento: Localized Time‐Warping for Spatio‐Temporal Selection
Author(s) -
Solteszova V.,
Smit N. N.,
Stoppel S.,
Grüner R.,
Bruckner S.
Publication year - 2020
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.13763
Subject(s) - computer science , temporal database , animation , dynamic time warping , clipping (morphology) , timestamp , event (particle physics) , domain (mathematical analysis) , artificial intelligence , computer vision , data mining , computer graphics (images) , real time computing , mathematical analysis , physics , linguistics , philosophy , mathematics , quantum mechanics
Interaction techniques for temporal data are often focused on affecting the spatial aspects of the data, for instance through the use of transfer functions, camera navigation or clipping planes. However, the temporal aspect of the data interaction is often neglected. The temporal component is either visualized as individual time steps, an animation or a static summary over the temporal domain. When dealing with streaming data, these techniques are unable to cope with the task of re‐viewing an interesting local spatio‐temporal event, while continuing to observe the rest of the feed. We propose a novel technique that allows users to interactively specify areas of interest in the spatio‐temporal domain. By employing a time‐warp function, we are able to slow down time, freeze time or even travel back in time, around spatio‐temporal events of interest. The combination of such a (pre‐defined) time‐warp function and brushing directly in the data to select regions of interest allows for a detailed review of temporally and spatially localized events, while maintaining an overview of the global spatio‐temporal data. We demonstrate the utility of our technique with several usage scenarios.