EuroVisShort2022
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Browsing EuroVisShort2022 by Author "Iuricich, Federico"
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Item Application-oriented Analysis of Material Interface Reconstruction Algorithms in Time-varying Bijel Simulations(The Eurographics Association, 2022) Bao, Xueyi; Karthikeyan, Nikhil; Schiller, Ulf D.; Iuricich, Federico; Agus, Marco; Aigner, Wolfgang; Hoellt, ThomasMultimaterial interface reconstruction has been investigated over the years both from visualization and analytical point of view using different metrics. When focusing on visualization, interface continuity and smoothness are used to quantify interface quality. When the end goal is interface analysis, metrics closer to the physical properties of the material are preferred (e.g., curvature, tortuosity). In this paper, we re-evaluate three Multimaterial Interface Reconstruction (MIR) algorithms, already integrated in established visualization frameworks, under the lens of application-oriented metrics. Specifically, we analyze interface curvature, particle-interface distance, and medial axis-interface distance in a time-varying bijel simulation. Our analysis shows that the interface presenting the best visual qualities is not always the most useful for domain scientists when evaluating the material properties.Item CellTrackVis: Analyzing the Performance of Cell Tracking Algorithms(The Eurographics Association, 2022) Li, Weimin; Zhang, Xiang; Stern, Alan; Birtwistle, Marc; Iuricich, Federico; Agus, Marco; Aigner, Wolfgang; Hoellt, ThomasLive-cell imaging is a common data acquisition technique used by biologists to analyze cell behavior. Since manually tracking cells in a video sequence is extremely time-consuming, many automatic algorithms have been developed in the last twenty years to accomplish the task. However, none of these algorithms can yet claim robust tracking performance at the varying of acquisition conditions (e.g., cell type, acquisition device, cell treatments). While many visualization tools exist to help with cell behavior analysis, there are no tools to help with the algorithm's validation. This paper proposes CellTrackVis, a new visualization tool for evaluating cell tracking algorithms. CellTrackVis allows comparing automatically generated cell tracks with ground truth data to help biologists select the best-suited algorithm for their experimental pipeline. Moreover, CellTackVis can be used as a debugging tool while developing a new cell tracking algorithm to investigate where, when, and why each tracking error occurred.