DocumentCode :
721381
Title :
An uncertainty-driven approach to vortex analysis using oracle consensus and spatial proximity
Author :
Biswas, Ayan ; Thompson, David ; Wenbin He ; Qi Deng ; Chun-Ming Chen ; Han-Wei Shenk ; Machiraju, Raghu ; Rangarajan, Anand
Author_Institution :
Ohio State Univ., Columbus, OH, USA
fYear :
2015
fDate :
14-17 April 2015
Firstpage :
223
Lastpage :
230
Abstract :
Although vortex analysis and detection have been extensively investigated in the past, none of the existing techniques are able to provide fully robust and reliable identification results. Local vortex detection methods are popular as they are efficient and easy to implement, and produce binary outputs based on a user-specified, hard threshold. However, vortices are global features, which present challenges for local detectors. On the other hand, global detectors are computationally intensive and require considerable user input. In this work, we propose a consensus-based uncertainty model and introduce spatial proximity to enhance vortex detection results obtained using point-based methods. We use four existing local vortex detectors and convert their outputs into fuzzy possibility values using a sigmoid-based soft-thresholding approach. We apply a majority voting scheme that enables us to identify candidate vortex regions with a higher degree of confidence. Then, we introduce spatial proximity- based analysis to discern the final vortical regions. Thus, by using spatial proximity coupled with fuzzy inputs, we propose a novel uncertainty analysis approach for vortex detection. We use expert´s input to better estimate the system parameters and results from two real-world data sets demonstrate the efficacy of our method.
Keywords :
computational fluid dynamics; flow visualisation; fuzzy set theory; uncertainty handling; vortices; binary outputs; confidence degree; consensus-based uncertainty model; fuzzy inputs; fuzzy possibility values; global detectors; local detectors; local vortex detectors; majority voting scheme; oracle consensus; point-based methods; real-world data sets; sigmoid-based soft-thresholding approach; spatial proximity-based analysis; system parameter estimation; uncertainty-driven approach; vortex analysis; vortex regions; Data visualization; Detectors; Electronic mail; Entropy; Robustness; Tensile stress; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visualization Symposium (PacificVis), 2015 IEEE Pacific
Conference_Location :
Hangzhou
Type :
conf
DOI :
10.1109/PACIFICVIS.2015.7156381
Filename :
7156381
Link To Document :
بازگشت