This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
A 2D Flow Visualization User Study Using Explicit Flow Synthesis and Implicit Task Design
May 2012 (vol. 18 no. 5)
pp. 783-796
ASCII Text
x 
 
Zhanping Liu, Shangshu Cai, J. Edward Swan, Robert J. Moorhead, J. P. Martin, T. J. Jankun-Kelly, "A 2D Flow Visualization User Study Using Explicit Flow Synthesis and Implicit Task Design," IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 5, pp. 783-796, May, 2012.
 
 
BibTex
x
 
@article{ 10.1109/TVCG.2011.110,
author = { Zhanping Liu and Shangshu Cai and J. Edward Swan and Robert J. Moorhead and J. P. Martin and T. J. Jankun-Kelly},
title = {A 2D Flow Visualization User Study Using Explicit Flow Synthesis and Implicit Task Design},
journal ={IEEE Transactions on Visualization and Computer Graphics},
volume = {18},
number = {5},
issn = {1077-2626},
year = {2012},
pages = {783-796},
doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2011.110},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Visualization and Computer Graphics
TI - A 2D Flow Visualization User Study Using Explicit Flow Synthesis and Implicit Task Design
IS - 5
SN - 1077-2626
SP783
EP796
EPD - 783-796
A1 - Zhanping Liu,
A1 - Shangshu Cai,
A1 - J. Edward Swan,
A1 - Robert J. Moorhead,
A1 - J. P. Martin,
A1 - T. J. Jankun-Kelly,
PY - 2012
KW - user interfaces
KW - data visualisation
KW - interpolation
KW - pattern classification
KW - statistical analysis
KW - flow representation
KW - 2D flow visualization user study
KW - explicit flow synthesis
KW - grid-based variable-size arrow
KW - streamlines variant
KW - line integral convolution variant
KW - colorwheel map
KW - rainbow color map
KW - geometry-based techniques
KW - texture-based techniques
KW - data-related bias reduction
KW - topological complexity
KW - pattern-based implicit task design
KW - critical point recognition
KW - critical point classification
KW - symmetric pattern categorization
KW - variable-duration measurement scheme
KW - fixed-duration measurement scheme
KW - lightweight precision-critical flow analysis task
KW - heavyweight judgment-intensive flow analysis task
KW - visualization effectiveness
KW - outliers
KW - Ryan REGWQ post-hoc homogeneous subset test
KW - statistical analysis
KW - texture-based dense representation
KW - geometry-based integral representation
KW - visual interpolation
KW - flow mental reconstruction
KW - Visualization
KW - Image color analysis
KW - Color
KW - Force
KW - Streaming media
KW - Synthesizers
KW - Electronic mail
KW - evenly spaced streamlines.
KW - Index Terms—Flow visualization
KW - user study
KW - visualization effectiveness
KW - flow synthesis
KW - task design
KW - test strategy
KW - LIC
VL - 18
JA - IEEE Transactions on Visualization and Computer Graphics
ER -
 
Zhanping Liu, Dept. of Comput. Sci., Kentucky State Univ., Frankfort, KY, USA
Shangshu Cai, Center for Risk Studies & Safety, Univ. of California at Santa Barbara, Goleta, CA, USA
J. Edward Swan, Dept. of Comput. Sci. & Eng., Mississippi State Univ., Starkville, MS, USA
Robert J. Moorhead, Electr. & Comput. Eng. Dept., Mississippi State Univ., Starkville, MS, USA
J. P. Martin, Lockheed Martin/U.S. Army Res. Lab., Aberdeen Proving Ground, MD, USA
T. J. Jankun-Kelly, Dept. of Comput. Sci. & Eng., Mississippi State Univ., Starkville, MS, USA
This paper presents a 2D flow visualization user study that we conducted using new methodologies to increase the objectiveness. We evaluated grid-based variable-size arrows, evenly spaced streamlines, and line integral convolution (LIC) variants (basic, oriented, and enhanced versions) coupled with a colorwheel and/or rainbow color map, which are representative of many geometry-based and texture-based techniques. To reduce data-related bias, template-based explicit flow synthesis was used to create a wide variety of symmetric flows with similar topological complexity. To suppress task-related bias, pattern-based implicit task design was employed, addressing critical point recognition, critical point classification, and symmetric pattern categorization. In addition, variable-duration and fixed-duration measurement schemes were utilized for lightweight precision-critical and heavyweight judgment-intensive flow analysis tasks, respectively, to record visualization effectiveness. We eliminated outliers and used the Ryan REGWQ post-hoc homogeneous subset tests in statistical analysis to obtain reliable findings. Our study shows that a texture-based dense representation with accentuated flow streaks, such as enhanced LIC, enables intuitive perception of the flow, while a geometry-based integral representation with uniform density control, such as evenly spaced streamlines, may exploit visual interpolation to facilitate mental reconstruction of the flow. It is also shown that inappropriate color mapping (e.g., colorwheel) may add distractions to a flow representation.

[1] R.S. Laramee, H. Hauser, H. Doleisch, B. Vrolijk, F.H. Post, and D. Weiskopf, "The State of the Art in Flow Visualization: Dense and Texture-Based Techniques," Computer Graphics Forum, vol. 23, no. 2, pp. 203-221, 2004.
[2] B. Cabral and L. Leedom, "Imaging Vector Fields Using Line Integral Convolution," Proc. ACM SIGGRAPH '93, pp. 263-270, 1993.
[3] T. McLoughlin, R.S. Laramee, R. Peikert, F.H. Post, and M. Chen, "Over Two Decades of Integration-Based, Geometric Vector Field Visualization," Proc. EuroGraphics '09, pp. 73-92, 2009.
[4] D.H. Laidlaw, R.M. Kirby, C.D. Jackson, J.S. Davidson, T.S. Miller, M.D. Silva, W.H. Warren, and M.J. Tarr, "Comparing 2D Vector Field Visualization Methods: A User Study," IEEE Trans. Visualization and Computer Graphics, vol. 11, no. 1, pp. 59-70, Jan./Feb. 2005.
[5] A. Forsberg, J. Chen, and D. Laidlaw, "Comparing 3D Vector Field Visualization Methods: A User Study," IEEE Trans. Visualization and Computer Graphics, vol. 15, no. 6, pp. 1219-1226, Nov./Dec. 2009.
[6] C. Ware, "Toward a Perceptual Theory of Flow Visualization," IEEE Computer Graphics and Applications, vol. 28, no. 2, pp. 6-11, Mar. 2008.
[7] C. Johnson, R. Moorhead, T. Munzner, H. Pfister, P. Rheingans, and T.S. Yoo, NIH/NSF Visualization Research Challenges, pp. 1-36. IEEE Computer Soc., 2006.
[8] J.J. van Wijk, "Image Based Flow Visualization," ACM Trans. Graphics, vol. 21, no. 3, pp. 745-754, 2002.
[9] J.J. van Wijk, "Image Based Flow Visualization for Curved Surfaces," Proc. IEEE Visualization (VIS '03), pp. 123-130, 2003.
[10] R.S. Laramee, J.J. van Wijk, B. Jobard, and H. Hauser, "ISA and IBFVS: Image Space Based Visualization of Flow on Surfaces," IEEE Trans. Visualization and Computer Graphics, vol. 10, no. 6, pp. 637-648, Nov./Dec. 2004.
[11] J. Helman and L. Hesselink, "Representation and Display of Vector Field Topology in Fluid Flow Data Sets," Computer, vol. 22, no. 8, pp. 27-36, Aug. 1989.
[12] F.H. Post, B. Vrolijk, H. Hauser, R.S. Laramee, and H. Doleisch, "The State of the Art in Flow Visualization: Feature Extraction and Tracking," Computer Graphics Forum, vol. 22, no. 4, pp. 775-792, 2003.
[13] R.S. Laramee, H. Hauser, L. Zhao, and F.H. Post, "Topology-Based Flow Visualization—The State of the Art," Proc. Visualization and Math., H. Hauser, H. Hagen, and H. Theisel, eds., pp. 1-19, 2007.
[14] E. Zhang, K. Mischaikow, and G. Turk, "Vector Field Design on Surfaces," ACM Trans. Graphics, vol. 25, no. 4, pp. 1294-1326, 2006.
[15] K.-L. Ma, B. Cabral, H.-C. Hege, V. Interrante, and D. Stalling, "Texture Synthesis with Line Integral Convolution," Proc. ACM SIGGRAPH '97, Course Notes, 1997.
[16] R. Wegenkittl, E. Groller, and W. Purgathofer, "Animating Flow Fields: Rendering of Oriented Line Integral Convolution," Proc. Computer Animation '97, pp. 15-21, 1997.
[17] A. Okada and D.L. Kao, "Enhanced Line Integral Convolution with Flow Feature Detection," Proc. IS&T/SPIE Electronics Imaging '97, pp. 206-217, 1997.
[18] Z. Liu, R.J. Moorhead,II, and J. Groner, "An Advanced Evenly Spaced Streamline Placement Algorithm," IEEE Trans. Visualization and Computer Graphics, vol. 12, no. 5, pp. 965-972, Sept./Oct. 2006.
[19] C. Ware, Information Visualization: Perception for Design. Morgan Kaufman Publisher, 2004.
[20] A. Johannsen and R.J. Moorhead,II, "AGP: Ocean Model Flow Visualization," IEEE Computer Graphics and Applications, vol. 15, no. 4, pp. 28-33, July 1995.
[21] G. Turk and D. Banks, "Image-Guided Streamline Placement," Proc. ACM SIGGRAPH '96, pp. 453-460, 1996.
[22] B. Jobard and W. Lefer, "Creating Evenly Spaced Streamlines of Arbitrary Density," Proc. Eighth Eurographics Workshop Visualization in Scientific Computing, pp. 45-55, 1997.
[23] H. Wainer and D. Thissen, "Graphical Data Analysis," A Handbook for Data Analysis in the Behavioral Sciences: Statistical Issues, G. Keren and C. Lewis, eds., pp. 391-458, Lawrence Erlbaum Assoc., 1993.
[24] M.E.J. Masson and G.R. Loftus, "Using Confidence Intervals for Graphically Based Data Interpolation," Canadian Experimental Psychology, vol. 57, no. 3, pp. 203-220, 2003.
[25] V. Barnett and T. Lewis, Outliers in Statistical Data, third ed. John Wiley and Sons, 1994.
[26] D.C. Howell, Statistical Methods for Psychology, fifth ed. Duxbury Publisher, 2002.
[27] Z. Liu and R.J. Moorhead,II, "Robust Loop Detection for Interactively Placing Evenly Spaced Streamlines," IEEE Computing in Science and Eng., vol. 9, no. 4, pp. 86-91, July 2007.
[28] K. Wu, Z. Liu, S. Zhang, and R.J. Moorhead,II, "Topology-Aware Evenly-Spaced Streamline Placement," IEEE Trans. Visualization and Computer Graphics, vol. 16, no. 5, pp. 791-801, Sept./Oct. 2010.
[29] J. Palacios and E. Zhang, "Rotational Symmetry Field Design on Surfaces," ACM Trans. Graphics, vol. 26, no. 3, 2007.
[30] N. Ray, B. Vallet, W.C. Li, and B. Levy, "N-Symmetry Direction Field Design," ACM Trans. Graphics, vol. 27, no. 2, 2008.

Index Terms:
user interfaces,data visualisation,interpolation,pattern classification,statistical analysis,flow representation,2D flow visualization user study,explicit flow synthesis,grid-based variable-size arrow,streamlines variant,line integral convolution variant,colorwheel map,rainbow color map,geometry-based techniques,texture-based techniques,data-related bias reduction,topological complexity,pattern-based implicit task design,critical point recognition,critical point classification,symmetric pattern categorization,variable-duration measurement scheme,fixed-duration measurement scheme,lightweight precision-critical flow analysis task,heavyweight judgment-intensive flow analysis task,visualization effectiveness,outliers,Ryan REGWQ post-hoc homogeneous subset test,statistical analysis,texture-based dense representation,geometry-based integral representation,visual interpolation,flow mental reconstruction,Visualization,Image color analysis,Color,Force,Streaming media,Synthesizers,Electronic mail,evenly spaced streamlines.,Index Terms—Flow visualization,user study,visualization effectiveness,flow synthesis,task design,test strategy,LIC
Citation:
Zhanping Liu, Shangshu Cai, J. Edward Swan, Robert J. Moorhead, J. P. Martin, T. J. Jankun-Kelly, "A 2D Flow Visualization User Study Using Explicit Flow Synthesis and Implicit Task Design," IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 5, pp. 783-796, May 2012, doi:10.1109/TVCG.2011.110
Usage of this product signifies your acceptance of the Terms of Use.