Skip to Main content Skip to Navigation
Journal articles

Feature Driven Combination of Animated Vector Field Visualizations

Abstract : Animated visualizations are one of the methods for finding and understanding complex structures of time‐dependent vector fields. Many visualization designs can be used to this end, such as streamlines, vector glyphs, and image‐based techniques. While all such designs can depict any vector field, their effectiveness in highlighting particular field aspects has not been fully explored. To fill this gap, we compare three animated vector field visualization techniques, OLIC, IBFV, and particles, for a critical point detection‐and‐classification task through a user study. Our results show that the effectiveness of the studied techniques depends on the nature of the critical points. We use these results to design a new flow visualization technique that combines all studied techniques in a single view by locally using the most effective technique for the patterns present in the flow data at that location. A second user study shows that our technique is more efficient and less error prone than the three other techniques used individually for the critical point detection task
Document type :
Journal articles
Complete list of metadata

Cited literature [74 references]  Display  Hide  Download
Contributor : Laurence Porte Connect in order to contact the contributor
Submitted on : Wednesday, July 29, 2020 - 9:18:57 AM
Last modification on : Wednesday, November 3, 2021 - 4:18:00 AM
Long-term archiving on: : Tuesday, December 1, 2020 - 7:24:19 AM




María-Jesús Lobo, Alexandru C Telea, Christophe Hurter. Feature Driven Combination of Animated Vector Field Visualizations. Computer Graphics Forum, Wiley, 2020, 39 (3), pp.429-441. ⟨10.1111/cgf.13992⟩. ⟨hal-02907118⟩



Record views


Files downloads