A Taxonomy of 3D y Occlusion Management T Techniques h i Niklas - - PowerPoint PPT Presentation

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A Taxonomy of 3D y Occlusion Management T Techniques h i Niklas Elmqvist (elm@cs.chalmers.se) Philippas Tsigas (tsigas@cs.chalmers.se) Philippas Tsigas (tsigas@cs.chalmers.se) Chalmers University of Technology A Common Denominator Where

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A Taxonomy of 3D y Occlusion Management T h i Techniques

Niklas Elmqvist (elm@cs.chalmers.se) Philippas Tsigas (tsigas@cs.chalmers.se) Philippas Tsigas (tsigas@cs.chalmers.se)

Chalmers University of Technology

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A Common Denominator…

Where is the target?

3D occlusion is a

big problem!

March 15, 2007 2

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Why a Taxonomy?

  • Occlusion is a fact of life in 3D
  • Visualization designers (us) deal with it routinely

– X-ray vision, bird’s eye views, World-in-Miniature, etc…

l i

h ( f ) – Occlusion management techniques (most often 3D)

  • But how? Motivation? Strategies?
  • Formalizing occlusion and occlusion management
  • Formalizing occlusion and occlusion management

– Provide common vocabulary – Facilitate comparison and benchmarking – Suggest suitable methods – Inform future research

March 15, 2007 3

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Taxonomy Design

  • What goes in a taxonomy?

g y

  • Use as a design space as well as for classification
  • Characteristics of occlusion management techniques?
  • Six primary dimensions:

– Primary Purpose Disambiguation Strength – Disambiguation Strength – Depth Cues – View Paradigm – Interaction Model – Target Invariances

March 15, 2007 4

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Taxonomy Dimensions (1)

  • Primary Purpose
  • Disambiguation Strength

y p

  • Why do we need this

technique?

g g

  • What can the technique

handle?

  • Domain: [discovery,

access, spatial relation]

  • Domain: [proximity,

intersection, enclosement, containment] containment]

March 15, 2007 5

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Taxonomy Dimensions (2)

  • Depth Cues
  • View Paradigm

p

  • How much depth

information is retained?

g

  • How are the views and view

space managed?

  • Domain: [low to high]
  • Domain:

[single/twin/multiple x int/sep]

March 15, 2007 6

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Taxonomy Dimensions (3)

  • I nteraction Model
  • Target I nvariances
  • How do users actually

activate the technique?

g

  • What is the visual impact
  • f the technique?
  • Domain: [active, passive,

hybrid]

  • Domain: yes/no for

[location, geometry, appearance] appearance]

March 15, 2007 7

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SLIDE 8

Classification

March 15, 2007 8

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Design Patterns

  • Analyze classifications of 25+ techniques

y q

  • Related trends crystallize – extract design patterns
  • Design pattern: [Alexander 1976]

– Generic and reusable solution to a commonly occurring problem

March 15, 2007 9

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Multiple Views

  • Provide additional 3D views to reduce occlusion
  • Characteristic techniques:

– CAD programs ld – Worlds in Miniature [Stoakley et al. 1995] – Worldlets [Elvins et al. 1997]

March 15, 2007 10

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Virtual X-Ray

  • Make interfering surfaces (semi-)transparent to show

g ( ) p hidden targets

  • Characteristic techniques:

– Perspective cutouts [Coffin and Höllerer 2006] – Interactive break-away [Diepstraten et al. 2003] – IDVR [Viola et al. 2004]

March 15, 2007 11

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Interactive Exploder

  • Interactively displace objects separating targets or

y p j p g g removing distractors

  • Characteristic techniques:

l b – 3D explosion probe [Sonnet et al. 2004] – Deformation-based volume explosion [McGuffin et al. 2003] – BalloonProbe [Elmqvist and Tudoreanu 2006]

March 15, 2007 12

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Projection Distorter

  • Integrate several 3D views into a single one in the view

g g (projection) space

  • Characteristic techniques:

l – Artistic multiprojection [Agrawala et al. 2000] – View projection animation

[Elmqvist and Tsigas 2006]

– Non-linear view projections

[Singh 2002] March 15, 2007 13

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Tour Planner

  • Build and take user on a grand tour that reveals the

g

whole 3D world

  • Characteristic techniques:

f d – Way-finder [Andújar et al. 2004] – Guided Web3D worlds [Chittaro et al. 2003] – Dog-on-a-leash [Wernert and Hanson 1999]

March 15, 2007 14

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The Future?

  • Patterns extracted from existing work

g

– Not complete, other patterns possible! – Example: scene index, view management, cutting planes

F t h di ti

  • Future research directions

– Combinations of patterns – Awareness – Previous interaction to inform target selection [Singh and Balakrishnan 2004]

  • Additional perceptual mechanisms
  • Additional perceptual mechanisms

– Augmented perception…

March 15, 2007 15

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Conclusions

  • Taxonomy for occlusion management

y g

– Classifying existing work and extract patterns – Suggest future research directions

St t

di ti i hi f t

  • Strategy space distinguishing factor:

– I mage space: virtual X-ray – View space: projection distorter and multiple viewports – Object space: interactive exploder – Temporal space: tour planner

  • Future: combinations awareness and hybrid interaction
  • Future: combinations, awareness and hybrid interaction

– More patterns?

March 15, 2007 16

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Questions?

Current Contact I nformation:

  • Niklas Elmqvist

INRIA Futurs/LRI Université Paris-Sud XI Université Paris-Sud XI elm@lri.fr

  • Philippas Tsigas

Department of Computer Science Chalmers University tsigas@cs.chalmers.se tsigas@cs.chalmers.se

http:/ / www.cs.chalmers.se/ ~ elm/ projects/ phd-thesis/

March 15, 2007 17

http:/ / www.cs.chalmers.se/ elm/ projects/ phd thesis/