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HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
HR3D: Content Adaptive Parallax Barriers
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HR3D: Content Adaptive Parallax Barriers

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HR3D: Content Adaptive Parallax Barriers, SIGGRAPH Asia 2010 Technical Paper presentation, presented by Douglas Lanman (http://web.media.mit.edu/~dlanman). Please see the project page for more …

HR3D: Content Adaptive Parallax Barriers, SIGGRAPH Asia 2010 Technical Paper presentation, presented by Douglas Lanman (http://web.media.mit.edu/~dlanman). Please see the project page for more details: http://web.media.mit.edu/~mhirsch/hr3d

This is a project in the Camera Culture group (http://cameraculture.media.mit.edu) at the MIT Media Lab, led by Professor Ramesh Raskar (http://web.media.mit.edu/~raskar).

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  • http://www.pc.rhul.ac.uk/staff/J.Zanker/PS1061/L4/PS1061_4.htmhttp://psychinaction.files.wordpress.com/2010/02/picture2.jpg
  • http://coolpics.911mb.com/galleries-coolpics/OpticalIllusions/WiggleVision/WiggleVision1.phphttp://www.brianharte.co.uk/blog/47-stereograms/http://prometheus.med.utah.edu/~bwjones/2009/03/focus-stacking/
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    • 1. Content-Adaptive Parallax Barriers for Automultiscopic 3D Display<br />Douglas Lanman Matthew Hirsch<br />Yunhee Kim Ramesh Raskar<br />MIT Media Lab<br />Imaging Hardware Session<br />Friday, 17 December | 4:15 PM – 6:00 PM | Room E1-E4<br />
    • 2. A Renewed Interest in 3D Displays<br />Theatrical and Home Movies<br />Consumer Electronics<br />A recent history of 3D displays<br /><ul><li> Avatar [released December 2009, has grossed >$2.7 billion so far]
    • 3. RealD Cinema, Dolby 3D, XpanD 3D, MasterImage 3D, etc.
    • 4. NVIDIA 3D Vision
    • 5. Nintendo 3DS</li></ul>Expansion of 3D to our living rooms, mobile phones, advertising, etc.<br />
    • 6. What is a 3D Display?<br />Monocular Depth Cues Supported by Conventional Photography<br /><ul><li> relative and familiar size
    • 7. perspective and occlusion
    • 8. texture gradient, shading and lighting, and atmospheric effects</li></li></ul><li>Binocular Depth Cues<br />“It being thus established that the mind perceives an object of three dimensions by means of the two dissimilar pictures projected by it on the two retinae, the following question occurs: What would be the visual effect of simultaneously presenting to each eye, instead of the object itself, its projection on a plane surface as it appears to that eye?”<br />Binocular Depth Cues<br /><ul><li> retinal disparity [Charles Wheatstone, 1838]
    • 9. convergence</li></li></ul><li>What is missing?<br />Additional Monocular Depth Cues<br /><ul><li> motion parallax [Hermann von Helmholtz, 1866]
    • 10. accommodation</li></li></ul><li>Conventional vs. Light Field Displays<br />Lenslet Array<br />Pinhole Array<br />u<br />s<br />Virtual Scene<br />Viewers<br />Display<br />Conventional displays are view-independent<br /><ul><li> Consider two-plane light field parameterization [Levoy and Hanrahan, 1996]
    • 11. Pixel intensity/color does not vary as a function of viewing angle</li></ul>Light field displays are view-dependent (automultiscopic)<br /><ul><li> Achieved with pinhole/lenslet array placed close to the display
    • 12. Trades decreased spatial resolution for increased angular resolution</li></ul>Frederic Ives. Parallax Stereogram and Process of Making the Same. 1903.<br />Gabriel Lippmann. Épreuves Réversibles Donnant la Sensation du Relief. 1908.<br />
    • 13. Previous Approaches<br />barrier<br />lenslet<br />sensor/display<br />sensor/display<br />Achieving Light Field (Automultiscopic) Display<br /><ul><li> Two alternatives for spatially-multiplexed light field display:
    • 14. Attenuating masks using parallax barriers [Ives, 1903]
    • 15. Refracting lenslet arrays [Lippmann, 1908]
    • 16. Barriers cause severe attenuation  dim displays
    • 17. Lenslets impose fixed trade-off between spatial and angular resolution
    • 18. Masks can be optimized to increase optical efficiency
    • 19. Enables flexible 3D displays with increased brightness and refresh rate</li></li></ul><li>Target 4D Light Field<br />
    • 20. Target 4D Light Field<br />viewer moves right<br />viewer moves up<br />
    • 21. Parallax Barrier Front Mask (1 of 9)<br />
    • 22. Parallax Barrier Rear Mask (1 of 9)<br />
    • 23. Outline<br /><ul><li>Introduction
    • 24. Content-Adaptive Parallax Barriers
    • 25. Implementation and Results
    • 26. Discussion and Future Work
    • 27. Conclusion</li></li></ul><li>Light Field Analysis of Barriers<br />k<br />L[i,k]<br />i<br />`<br />k<br />g[k]<br />i<br />L[i,k]<br />f[i]<br />light box<br />
    • 28. Time-Multiplexing using Shifted Pinholes<br />L[i,k]<br />`<br />k<br />g[k]<br />i<br />f[i]<br />light box<br />Ken Perlinet al. An Autosteroscopic Display. 2000.<br />Yunhee Kim et al. Electrically Movable Pinhole Arrays. 2007.<br />
    • 29. Content-Adaptive Parallax Barriers<br />L[i,k]<br />`<br />k<br />g[k]<br />i<br />f[i]<br />light box<br />
    • 30. Content-Adaptive Parallax Barriers<br />`<br />=<br />
    • 31. Content-Adaptive Parallax Barriers<br />`<br />=<br />
    • 32. Content-Adaptive Parallax Barriers<br />`<br />=<br />
    • 33. Content-Adaptive Parallax Barriers<br />`<br />=<br />
    • 34. Target 4D Light Field<br />viewer moves right<br />viewer moves up<br />
    • 35. Optimization: Iteration 1<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />reconstruction (central view)<br />Daniel Lee and Sebastian Seung. Non-negative Matrix Factorization. 1999.<br />Vincent Blondel et al. Weighted Non-negative Matrix Factorization. 2008.<br />
    • 36. Optimization: Iteration 10<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />reconstruction (central view)<br />Daniel Lee and Sebastian Seung. Non-negative Matrix Factorization. 1999.<br />Vincent Blondel et al. Weighted Non-negative Matrix Factorization. 2008.<br />
    • 37. Optimization: Iteration 20<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />reconstruction (central view)<br />Daniel Lee and Sebastian Seung. Non-negative Matrix Factorization. 1999.<br />Vincent Blondel et al. Weighted Non-negative Matrix Factorization. 2008.<br />
    • 38. Optimization: Iteration 30<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />reconstruction (central view)<br />Daniel Lee and Sebastian Seung. Non-negative Matrix Factorization. 1999.<br />Vincent Blondel et al. Weighted Non-negative Matrix Factorization. 2008.<br />
    • 39. Optimization: Iteration 40<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />reconstruction (central view)<br />Daniel Lee and Sebastian Seung. Non-negative Matrix Factorization. 1999.<br />Vincent Blondel et al. Weighted Non-negative Matrix Factorization. 2008.<br />
    • 40. Optimization: Iteration 50<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />reconstruction (central view)<br />Daniel Lee and Sebastian Seung. Non-negative Matrix Factorization. 1999.<br />Vincent Blondel et al. Weighted Non-negative Matrix Factorization. 2008.<br />
    • 41. Optimization: Iteration 60<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />reconstruction (central view)<br />Daniel Lee and Sebastian Seung. Non-negative Matrix Factorization. 1999.<br />Vincent Blondel et al. Weighted Non-negative Matrix Factorization. 2008.<br />
    • 42. Optimization: Iteration 70<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />reconstruction (central view)<br />Daniel Lee and Sebastian Seung. Non-negative Matrix Factorization. 1999.<br />Vincent Blondel et al. Weighted Non-negative Matrix Factorization. 2008.<br />
    • 43. Optimization: Iteration 80<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />reconstruction (central view)<br />Daniel Lee and Sebastian Seung. Non-negative Matrix Factorization. 1999.<br />Vincent Blondel et al. Weighted Non-negative Matrix Factorization. 2008.<br />
    • 44. Optimization: Iteration 90<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />reconstruction (central view)<br />Daniel Lee and Sebastian Seung. Non-negative Matrix Factorization. 1999.<br />Vincent Blondel et al. Weighted Non-negative Matrix Factorization. 2008.<br />
    • 45. Content-Adaptive Front Mask (1 of 9)<br />
    • 46. Content-Adaptive Rear Mask (1 of 9)<br />
    • 47. Emitted 4D Light Field<br />
    • 48. Benefits of Content-Adaptation<br />1) Increasing brightness:<br />2) Increasing refresh rate:<br />
    • 49. Outline<br /><ul><li>Introduction
    • 50. Content-Adaptive Parallax Barriers
    • 51. Implementation and Results
    • 52. Discussion and Future Work
    • 53. Conclusion</li></li></ul><li>Implementation<br />Components<br /><ul><li>22 inch ViewSonic FuHzion VX2265wm LCD [1680×1050 @ 120 fps]</li></li></ul><li>Motion Parallax<br />viewer moves right<br />viewer moves up<br />Light Field<br />
    • 54.
    • 55.
    • 56. Increasing Brightness and Refresh Rate<br />1) Increasing brightness:<br />2) Increasing refresh rate:<br />
    • 57. Increasing Brightness and Refresh Rate<br />1) Increasing brightness:<br />2) Increasing refresh rate:<br />
    • 58. Increasing Brightness<br />Time-Shifted Barriers (central view)<br />Content-Adaptive Barriers (central view)<br />
    • 59. Increasing Refresh Rate<br />Time-Shifted Barriers (central view)<br />Content-Adaptive Barriers (central view)<br />
    • 60. Outline<br /><ul><li>Introduction
    • 61. Content-Adaptive Parallax Barriers
    • 62. Implementation and Results
    • 63. Discussion and Future Work
    • 64. Conclusion</li></li></ul><li>Future Work: Analytic Adaptation?<br />rear mask: f1[i,j]<br />front mask: g1[k,l]<br />What patterns does content-adaptation produce?<br /><ul><li> Optimization appears to produce local parallax barriers</li></li></ul><li>Future Work: Analytic Adaptation?<br />viewer moves right (b)<br />viewer moves up (a)<br />Light Field<br />(step edge)<br />Rear mask<br />Front mask<br />What patterns does content-adaptation produce?<br /><ul><li> Optimization appears to produce local parallax barriers
    • 65. Related to aperture problem(i.e., motion of windowed grating)
    • 66. NMF converges to local stationary point, not global minimum
    • 67. Emergent structure predicted by angular gradient:</li></ul>David Marr and Shimon Ullman. Directional Selectivity and Its Use in Early Visual Processing. 1981.<br />
    • 68. Future Work: Local Parallax Barriers<br />viewer moves right (b)<br />viewer moves up (a)<br />Light Field<br />Streamlines of the Angular Gradient*<br />Rear Mask<br />Front Mask<br />*Brian Cabral and Leith Casey Leedom. Imaging Vector Fields using Line Integral Convolution. 1993.<br />
    • 69. Outline<br /><ul><li>Introduction
    • 70. Content-Adaptive Parallax Barriers
    • 71. Implementation and Results
    • 72. Discussion and Future Work
    • 73. Conclusion</li></li></ul><li>Conclusion<br />`<br />Content-Adaptive Parallax Barriers<br />=<br /><ul><li> Described a rank constraint for all dual-layer displays
    • 74. With a fixed pair of masks, emitted light field is rank-1
    • 75. Achieved higher-rank approximation using temporal multiplexing
    • 76. With T time-multiplexed masks, emitted light field is rank-T
    • 77. Constructed a prototype using off-the-shelf panels
    • 78. Demonstrated light field display is a matrix approximation problem
    • 79. Introduced content-adaptive parallax barriers
    • 80. Applied weighted NMF to optimize weighted Euclidean distance to target</li></ul>Adaptation increases brightness and refresh rate of dual-stacked LCDs<br />
    • 81. Questions and Answers<br />Content-Adaptive Parallax Barriers<br />“Can we request that Photography renders the full variety offered by the direct observation of objects? Is it possible to create a photographic print in such a manner that it represents the exterior world framed, in appearance, between the boundaries of the print, as if those boundaries were that of a window opened on reality? It appears that yes, we can request from Photography infinitely more than from the human hand.”<br />Gabriel Lippmann, 1908<br />

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