High-quality animation of 2d steady vector fields

Lefer, Wilfrid; Jobard, Bruno; Leduc, Claire

doi:10.1109/tvcg.2004.1260754

Cited by 18 publications

(13 citation statements)

References 20 publications

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“…Yet many authors have proposed that animation should provide an effective method for flow visualization. Animation techniques include color table animation [Jobard and Lefer, 1997;Lefer et al 2004;Laramee et al 2004] where cycling through a color look up table causes a visual pattern to move over a field. The line integral convolution (LIC) method has also frequently been animated (e.g.…”

Section: Effective Display Of Vector Fieldsmentioning

confidence: 99%

Animated versus static views of steady flow patterns

Ware

Bolan

Miller

et al. 2016

Proceedings of the ACM Symposium on Applied Perception

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Two experiments were conducted to test the hypothesis that animated representations of vector fields are more effective than common static representations even for steady flow. We compared four flow visualization methods: animated streamlets, animated orthogonal line segments (where short lines were elongated orthogonal to the flow direction but animated in the direction of flow), static equally spaced streamlines, and static arrow grids. The first experiment involved a pattern detection task in which the participant searched for an anomalous flow pattern in a field of similar patterns. The results showed that both the animation methods produced more accurate and faster responses. The second experiment involved mentally tracing an advection path from a central dot in the flow field and marking where the path would cross the boundary of a surrounding circle. For this task the animated streamlets resulted in better performance than the other methods, but the animated orthogonal particles resulted in the worst performance. We conclude with recommendations for the representation of steady flow patterns.

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Section: Effective Display Of Vector Fieldsmentioning

confidence: 99%

Animated versus static views of steady flow patterns

Ware

Bolan

Miller

et al. 2016

Proceedings of the ACM Symposium on Applied Perception

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“…Lefer et al provide a novel technique for producing variable-speed animations [LJL04]. This method encodes the motion information in a so-called motion map and a color table is utilized to animate the streamlines.…”

Section: Streamlines In 2d Steady-state Flow Fieldsmentioning

confidence: 99%

Over Two Decades of Integration‐Based, Geometric Flow Visualization

McLoughlin

Laramee

Peikert

et al. 2010

Computer Graphics Forum

270

160

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Flow visualization is a fascinating sub-branch of scientific visualization. With ever increasing computing power, it is possible to process ever more complex fluid simulations. However, a gap between data set sizes and our ability to visualize them remains. This is especially true for the field of flow visualization which deals with large, timedependent, multivariate simulation datasets. In this paper, geometry based flow visualization techniques form the focus of discussion. Geometric flow visualization methods place discrete objects in the vector field whose characteristics reflect the underlying properties of the flow. A great amount of progress has been made in this field over the last two decades. However, a number of challenges remain, including placement, speed of computation, and perception. In this survey, we review and classify geometric flow visualization literature according to the most important challenges when considering such a visualization, a central theme being the seeding object upon which they are based. This paper details our investigation into these techniques with discussions on their applicability and their relative merits and drawbacks. The result is an up-to-date overview of the current state-of-the-art that highlights both solved and unsolved problems in this rapidly evolving branch of research. It also serves as a concise introduction to the field of flow visualization research.

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“…There has been significant research on flow visualization including geometry-/glyph-based methods 1 such as arrow plots, streamlines 2,3,4 and stream surfaces as well as texture-/image-based techniques 5 , e.g., Line Integral Convolution (LIC) 6 and LEA 7 . Animation is not only an instrumental tool for enhancing the display of spatial correlation such as flow direction, orientation (positive flow direction), and topology but also an intuitive cue for improving the understanding of temporal characteristics like velocity magnitude and flow evolution (e.g., in terms of convergence/divergence) over time.…”

Section: Introductionmentioning

confidence: 99%

“…There are several challenges for 2D flow animation. Spatial continuity, favored in both tangential and orthogonal directions, facilitates mental reconstruction of the flow even from a geometric representation 2,3,4 . Insufficient continuity may prevent salient features from being recognized since an instantaneous frame leaves less time than provided by a still image for accurate comprehension.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, image contrast usually involves the use of color as the latter can have a great influence on the former. Temporal coherence, imposed on texture synthesis 7 and layout of geometric elements 4 , allows smooth inter-frame transition to be established from visual retention. Failure to address this issue incurs cluttering and flickering problems, affecting perception of the underlying flow structure.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Animating streamlines with repeated asymmetric patterns for steady flow visualization

Yeh

Liu

Lee

2012

Visualization and Data Analysis 2012

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Animation provides intuitive cueing for revealing essential spatial-temporal features of data in scientific visualization. This paper explores the design of Repeated Asymmetric Patterns (RAPs) in animating evenly-spaced color-mapped streamlines for dense accurate visualization of complex steady flows. We present a smooth cyclic variable-speed RAP animation model that performs velocity (magnitude) integral luminance transition on streamlines. This model is extended with inter-streamline synchronization in luminance varying along the tangential direction to emulate orthogonal advancing waves from a geometry-based flow representation, and then with evenly-spaced hue differing in the orthogonal direction to construct tangential flow streaks. To weave these two mutually dual sets of patterns, we propose an energy-decreasing strategy that adopts an iterative yet efficient procedure for determining the luminance phase and hue of each streamline in HSL color space. We also employ adaptive luminance interleaving in the direction perpendicular to the flow to increase the contrast between streamlines.

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High-quality animation of 2d steady vector fields

Cited by 18 publications

References 20 publications

Animated versus static views of steady flow patterns

Animated versus static views of steady flow patterns

Over Two Decades of Integration‐Based, Geometric Flow Visualization

Animating streamlines with repeated asymmetric patterns for steady flow visualization

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