perceptually based depth-ordering enhancement for direct volume rendering
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Perceptually Based Depth-Ordering Enhancement for Direct Volume
Rendering Lin Zheng, Yingcai Wu, and Kwan-Liu Ma
VIDI Research Group, UC Davis
Introduction
• Depth Perception: • visual ability to perceive the distance of 3D objects.
• Depth cues
Binocular CuesMonocular Cues
Occlusions Size Shading Stereopsis Disparity
Introduction
• In many visualizations, the depth ordering is ambiguous.• If there is no interaction:• static images on the magazine• posters
• Possible approaches:• Perspective projection• Halos, shadows, warm/cool color
Neghip
Related Work: Halos
• Enhancing Depth-Perception with Flexible Volumetric Halos, Stefan Bruckner and M. Eduard Gröller, 2007
• Depth-Dependent Halos: Illustrative Rendering of Dense Line Data, MH Evert and etc., 2009
Related Work: Warm/Cool Color
• Color Design for Illustrative Visualization, L. Wang, J. Giesen, K.T. McDonnell, P. Zolliker, and K. Mueller, 2008
Perception Models
• Only change the inherent factors: Luminance, opacity• We introduce two major models for depth perception:• X-junction Model• Transmittance Anchoring Principle (TAP)
• X-junction Model has limitation• TAP can be a complement
X-Junction Model: C-configuration
• Which layer is in the front• A or B?• Luminance(s)• > Luminance (r)• > Luminance (p)• > Luminance (q)• The luminance
decreasing in a “C” configuration.
X-Junction Model: A-configuration
• Which layer is in the front• Luminance (r) = (q)• The Luminance decreasing
order can be s>r=q>p• Or s>q=r>p• A-ambiguity
X-Junction Model: Z-configuration
• Luminance s>r>q>p• The luminance decreasing
in a “Z”-configuration• Still ambiguous?• + TAP model
Application of Perception Models
• TAP: the highest contrast is perceived to be at the background• Applying X-junction Model and TAP Model.• Improve A-ambiguity to Z-configuration, then to C-configuration
Z-configuration C-configurationA-ambiguity
Energy Function Design
• Three terms :
• Enhance the Perceived Depth Ordering• Keep the Perceived Transparency• Keep the Image Faithfulness
depth ordering transparency image faithfulness
Energy Function Design
• Perceived Depth Ordering:configuration of the junction area• Wrong C-configuration will not appear in semi-transparent structure• Four configurations (in DVR):• Wrong Z-configurations
• A configuration (A-ambiguity)
• Correct Z-configuration
• Correct C-configuration
Energy Function Design
• Perceived Transparency:
Metelli’s episcotister modelLuminance of transparent layers
Information EntropyConditional entropy
• Image Faithfulness:
Optimization
NO
Optimal
User Study
• Design:• A between-subjects study (12 subjects)• 60 cases total: 30 enhanced and 30 original
• Fisher’s exact test• Users were significantly more accurate in
enhanced cases: P-value = 0.0016
task interface
Results: neghip
• Although the difference is subtle, our user study shows that enhancement improves depth perception significantly
initial enhanced
Results: neghip
initial enhanced
Results: neghip
initial enhanced
Results: vortex dataset
initial enhanced
Results initial enhanced
Discussion
• + Easy to be embedded in current visualization system• + Luminance as the visual cue:• a primary visual cue in visual psychology• does not introduce additional overhead
• - Limitations of perception models:• deal with two overlapping layers at a time• do not work for enclosing and separate structures• consistency problem with intertwined structures
Conclusion and Future Work
• Investigated how to perceptually enhance depth ordering• Used perception models for quantitative measurement• Depth ordering (X-junction Model, TAP)• Image quality (Metelli episcotic Model)
• Designed an optimization framework for enhancing depth perception
• Conducted a user study showing the effectiveness of our approach• Future work: animation
Thank you!
• This research has been sponsored in part by the US National Science Foundation (NSF) through grant CCF-0811422 and US Department of Energy (DOE) with award DE-SC0002289.
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