The study of 3D flow fields is an emerging trend among researchers working in the area of fluid dynamics. They study visualizations of varying streamline positions and densities in balancing coverage, occlusion, and complexity.

The authors propose a deformation framework for focus+context (F+C) visualization of large and complex 3D streamline positions. This method manipulates streamline positions to reduce occlusion and clutter around the focal regions instead of varying streamline densities. It repositions the streamlines guided by deformed blocks partitioned from the volume space of flow fields. The framework minimizes the objective function maintaining volume boundary and edge flipping constraints, and expands and smooths blocks into energy terms. The authors further explain 3D flow field data along dynamic F+C using a graphics processing unit (GPU) linear system solver.

The authors engaged five researchers with experience in fluid dynamics, two postdoctoral scholars, one PhD student, and two master students, for two to two-and-a-half hours, to complete the study and to write comments. The method amplifies focus streamlines and minimizes the distortion simultaneously, and unlike the fisheye F+C technique, it uses both automatic and manual feature specifications for focus selection and effective visualization.

The framework suffers from several limitations. First, introducing streamline-based distortion measure could preserve streamline shapes and maintain the flow field patterns. Second, for the best visualization of results, easy and automatic parameter value selection is still needed. Third, integrating visualization transparency in the framework would reduce the occlusions of the dense streamlines. Fourth, error estimation produces scalar values.

The authors propose the real-time use of the method because of its effective visual understanding of streamlines. Overall, the paper is worth reading.