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wedge

Sean Gustafson Patrick Baudisch Carl Gutwin Pourang Irani. wedge. clutter-free visualization of off-screen locations. wedge. halo: clutter problem. wedge: avoids overlap. rel. ated. work. overviews. [Plaisant 95 and many others]. fisheye views.

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wedge

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  1. Sean Gustafson Patrick Baudisch Carl Gutwin Pourang Irani wedge clutter-free visualization of off-screen locations

  2. wedge halo: clutter problem wedge: avoids overlap

  3. rel ated work

  4. overviews [Plaisant 95 and many others]

  5. fisheye views fisheye views [Carpendale 01]

  6. edgeradar [Gustafson 07]

  7. simple arrows [Tecmo Bowl 87]

  8. scaled and stretched arrows [Burigat 06]

  9. city lights “space-efficient fisheye technique” [Mackinlay 03]

  10. halo [Baudisch 03]

  11. halo [Baudisch 03]

  12. th e problem

  13. the problem: clutter

  14. the problem: clutter

  15. (also not great: corners) side corner

  16. initial approaches clustering ovals Baudisch & Rosenholtz Irani et al. cut lines color separatevisually

  17. separate geometrically • circles offer only a single degree of freedom: radius (aka intrusion) • in some cases varying allows resolving overlap,in others it does not • how can we get additional degrees of freedom?

  18. th e wedge

  19. wedge base base base base leg leg target

  20. halo wedge

  21. 3 degrees of freedom intrusion aperture rotation

  22. rotation aperture avoiding overlap intrusion

  23. lay out algorithm

  24. avoidance algorithm

  25. avoidance algorithm

  26. avoidance algorithm

  27. avoidance algorithm

  28. avoidance algorithm

  29. leaves 2 degrees intrusion ~ distance base-width ~ distance

  30. wedge demo

  31. u ser study

  32. two interface conditions halo and wedge

  33. task 1: locate same as original halo paper halo wedge

  34. task 2: closest same as original halo paper halo wedge

  35. task 3: avoid same as original halo paper halo wedge

  36. IV: density sparse dense same as original halo paper = dense, remapped to bottom left corner

  37. 16 participants

  38. hypotheses • 1. wedge is more accurate • larger improvement in dense condition • larger improvement in corners • (no hypothesis about task time)

  39. results

  40. no significant difference in task time

  41. participants were significantly more accurate when using the wedge

  42. error in pixels Side Halo 60 Wedge 40 20 0 Dense Sparse locate task

  43. error in pixels Side Corner Halo 60 Wedge 40 20 0 Dense Sparse Dense Sparse locate task

  44. hypotheses  • 1. wedge is more accurate • larger improvement in dense condition • larger improvement in corners 

  45. wedge= uni fied pointing

  46. intrusion  0 citylights

  47. aperture  0 stretched arrows

  48. ? halo

  49. distance information in corner distance information along arc round bases

  50. aperture  360 halo

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