Illustrative visualization of time-varying features in spatio-temporal data. (October 2018) - Wu, Xiangyang; Chen, Zixi; Gu, Yuhui; Chen, Weiru; Fang, Mei-e
Abstract: Identifying and analyzing the time-varying features is important for understanding the spatio-temporal datasets. While there are numerous studies on illustrative visualization, existing solutions can hardly show subtle variations in a temporal dataset. This paper introduces a novel illustrative visualization scheme that employs temporal filtering techniques to disclose desired tiny features, which are further enhanced by an adaptive temporal illustration technique. The unconcerned context can be suppressed in a similar fashion. We develop a visual exploration system that empowers users to interactively manipulate and analyze temporal features. The experimental results on a mobile calling data demonstrate the effectivity and usefulness of our method.