“Occlusion”

1. “Occlusion” Prepared by: Shreya Rawal

2. Extending Distortion Viewing from 2D to 3D S. Carpendale, D. J. Cowperthwaite and F. David Fracchia (1997)

3. 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.

4. Various viewing techniques for 3D data • Viewing angle (rotation) • Viewing position (navigation) • Combination of the two

5. Problems associated • Loss of context • Loss of orientation • “Occlusion”

6. 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

7. Two – dimensional distortion patterns • Stretch orthogonal • Nonlinear orthogonal • Nonlinear radial • Step orthogonal

8. 2D Displacement + Magnification Stretch orthogonal Stretching all data on either of the two axes centered a the focus. Compressing the remaining areas uniformly.

9. 2D Displacement + Magnification 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

10. 2D Displacement + Magnification Nonlinear radial Adjacent edges curve away from the focus. Outer rows of the grid is hardly affected.

11. 2D Displacement + Magnification Step Orthogonal Data is aligned with the focus unstretched. Less data distortion. Disadvantage: Leaves unused space. Causes grouping of the data.

12. Displacement + Magnification • 2D • 3D

13. Magnification + Displacement vs. Displacement only in 2D 2D Displacement + Magnification 2D only Displacement Stretch Non-Linear Non-linear Step orthogonal orthogonal Radial Orthogonal In 2D: Magnification + Displacement has the same effect as Displacement only

14. Magnification + Displacement vs. Displacement only in 3D • Magnification + Displacement • Only- Displacement Stretch Non-Linear Non-linear Step orthogonal orthogonal Radial Orthogonal In 3D: Displacement only had better effects than Magnification + Displacement

15. 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

16. Visual Access Distortion viewer viewer

17. Single Focus

18. Multiple Foci

19. Randomly positioned nodes: • Close to real data.

20. EdgeLens: An interactive Method for Managing Edge Congestion in Graphs N. Wong, S. Carpendale, S. Greenberg (2003)

21. 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

22. Managing edge layout Edge density Crossovers Occlusion Airline routes from NorthWest Airlines, November, 2001

23. Edge congestion problem • Although position of node add value to visualization they introduce ambiguity (edge occlusion). Possible interpretations A simple 3 node graph

24. Solutions: Edge congestion problem • Layout • Position of nodes have importance. • Curving edges globally

25. 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

26. Solutions: Edge congestion problem • Magnification:

27. 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

28. Two EdgeLens approaches • Bubble Vs Spline a) Bubble b) Spline

29. 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

30. Algorithm Curved Edge Original position of edge • Decide which edges affected • Calculate displacements • Calculate spline control points (c1, c2) • Draw curves

31. Features and Demo • Video

32. 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)

33. 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, SheelaghCarpendale 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

34. 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