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“Occlusion”

Prepared by: Shreya Rawal

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Extending Distortion Viewing from 2D to 3D

S. Carpendale, D. J. Cowperthwaite and F. David Fracchia (1997)

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What after developing visualization?

Exploration Navigation Interpretation of data

We will be applying techniques which are used in 2D into 3D for exploration/navigation/interpretation.

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Various viewing techniques for 3D data

Viewing angle (rotation) Viewing position (navigation) Combination of the two

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Problems associated

Loss of context Loss of orientation “Occlusion”

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What is detail-in-context distortion?

You provide details but keep the context intact.

Distortion: Spatial reorganization of an existing representation Main aim is to minimize occlusion Applied with Magnification + Displacement

160 Nodes

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Two – dimensional distortion patterns

Stretch orthogonal Nonlinear orthogonal Nonlinear radial Step orthogonal

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Stretch orthogonal

• Stretching all data on either of the two axes centered a the focus.

• Compressing the remaining areas uniformly.

2D Displacement + Magnification

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Nonlinear orthogonal

• Focus is magnified to requested amount.

• Magnification decreases according to some function.

Disadvantages:

• Limits the magnification in focal region

• Causes more extreme compression at the edges

2D Displacement + Magnification

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Nonlinear radial

• Adjacent edges curve away from the focus.

• Outer rows of the grid is hardly affected.

2D Displacement + Magnification

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Step Orthogonal

• Data is aligned with the focus unstretched.

• Less data distortion.

Disadvantage:

• Leaves unused space.

• Causes grouping of the data.

2D Displacement + Magnification

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Displacement + Magnification

2D

3D

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• 2D Displacement + Magnification

• 2D only Displacement

Magnification + Displacement vs. Displacement only in 2D

In 2D: Magnification + Displacement has the same effect as Displacement only

Stretch Non-Linear Non-linear Steporthogonal orthogonal Radial Orthogonal

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Magnification + Displacement vs. Displacement only in 3D

Magnification +Displacement

Only-Displacement

In 3D: Displacement only had better effects than Magnification + Displacement

Stretch Non-Linear Non-linear Steporthogonal orthogonal Radial Orthogonal

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Visual Access Distortion Naïve 2D 3D extension still does not solve

Occlusion problem completely Solution

move geometry according to viewpoint magnify focus only displace items in a different way (curves vs.

straight lines) Focus + context approach

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Visual Access Distortion

viewerviewer

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Single Focus

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Multiple Foci

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Randomly positioned nodes:

Close to real data.

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EdgeLens: An interactive Method for Managing Edge Congestion in Graphs

N. Wong, S. Carpendale, S. Greenberg (2003)

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Problems in Graph representation

When dealing with complex and large real world dataset Many interconnected nodes leads to Edge-

congestion Edge-congestion results in:

obscuring nodes obscuring individual edges obscuring visual information

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Managing edge layout

1. Edge density

2. Crossovers

3. Occlusion

Airline routes from NorthWest Airlines, November, 2001

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Edge congestion problem Although position of node add value to

visualization they introduce ambiguity (edge occlusion).

A simple 3 node graph

Possible interpretations

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Solutions: Edge congestion problem

Layout Position of nodes have importance. Curving edges globally

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Solutions: Edge congestion problem Filtering

Removing unimportant edges only works where we can distinguish between important

and unimportant edges. you loose the relation of one edge with other edges

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Solutions: Edge congestion problem Magnification:

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EdgeLens: An interactive technique

It moves edges without detaching it from node Use displacement only

Respects the semantics of node layout. Disambiguates edge overlapping Disambiguates node overlapping Clarifies details about graph structure

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Two EdgeLens approaches Bubble Vs Spline

a) Bubbleb) Spline

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User Study 16 participants Task: 8 route finding task (easy, medium-easy,

medium and hard) Post session Questionnaire Data:

nodes: Canadian cities edges: Airline routes

Result: Spline turned out to be better

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Algorithm

• Decide which edges affected • Calculate displacements • Calculate spline control points (c1, c2) • Draw curves

Curved Edge

Original position of edge

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Features and Demo Video

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Discussion

Scalability of multiple focus points for technique discussed in 1st paper (distortion viewing) as compared to EdgeLens.

Distortion viewing (in 1st paper) can be applied to all kinds of 3D visualizations.

Can Occlusion be completely avoided in 3D? Deal Occlusion or Get rid of Occlusion? Detail in context!! (Bubble vs. Spline)

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References S. Carpendale, D.J. Cowperthwaite, F. David Fracchia.

Extending Distortion Viewing from 2D to 3D. IEEE Computer Graphics and Applications, 17(4), pp. 42-51, July / August 1997.

Nelson Wong, Sheelagh Carpendale and Saul Greenberg. EdgeLens: An Interactive Method for Managing Edge Congestion in Graphs. In Proceedings of IEEE Symposium on Information Visualization (InfoVis 2003). IEEE Press, pages 51-58, 2003

http://innovis.cpsc.ucalgary.ca/Research/EdgeLens http://www.cs.ubc.ca/~tmm/courses/cpsc533c-06-fall/

slides/depth-4x4.pdf

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My Project: Erlang trace data:

nodes: processes edges: interaction between processes (message

sending and spawning)

Position of nodes does not have any significance Hence concept of EdgeLens might not be applicable Yes, node occlusion and edge congestion is an issue