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776 Computer Vision

776 Computer Vision

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776 Computer Vision

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  1. 776 Computer Vision Jan-Michael Frahm, Enrique Dunn Spring 2013

  2. Last class

  3. Last Class 3Dpoint(4x1) World to camera coord. trans. matrix(4x4) 2D point(3x1) Camera to pixel coord. trans. matrix (3x3) Perspectiveprojection matrix(3x4) =

  4. Facing Real Cameras • There are undesired effects in real situations • perspective distortion • Camera artifacts • aperture is not infinitely small • lens • vignetting

  5. Radial Distortion • Caused by imperfect lenses • Deviations are most noticeable near the edge of the lens No distortion Pin cushion Barrel slide: S. Lazebnik

  6. Radial Distortion (xu, yu) undistorted image point as in ideal pinhole camera (xd,yd) distorted image point of camera with radial distortion (xc,yc) distortion center Kn n-th radial distortion coefficient Pn n-th tangential distortion coefficient • Brown’s distortion model • accounts for radial distortion • accounts for tangential distortion (distortion caused by lens placement errors) • typically K1 is used or K1, K2, P1, P2

  7. Facing Real Cameras • There are undesired effects in real situations • perspective distortion • Camera artifacts • aperture is not infinitely small • lens • vignetting, radial distortion

  8. Depth of Field http://www.cambridgeincolour.com/tutorials/depth-of-field.htm Slide by A. Efros

  9. How can we control the depth of field? • Changing the aperture size affects depth of field • A smaller aperture increases the range in which the object is approximately in focus • But small aperture reduces amount of light – need to increase exposure Slide by A. Efros

  10. F Number of the Camera f number (f-stop) ratio of focal length to aperture

  11. Varying the aperture Large aperture = small DOF Small aperture = large DOF Slide by A. Efros

  12. Facing Real Cameras • There are undesired effects in real situations • perspective distortion • Camera artifacts • aperture is not infinitely small • lens • vignetting, radial distortion • depth of field

  13. Field of View What does FOV depend on? Slide by A. Efros

  14. Field of View f f FOV depends on focal length and size of the aperture Smaller FOV = larger Focal Length Slide by A. Efros

  15. Field of View / Focal Length Large FOV, small f Camera close to car Small FOV, large f Camera far from the car Sources: A. Efros, F. Durand

  16. Same effect for faces standard wide-angle telephoto Source: F. Durand

  17. The dolly zoom http://en.wikipedia.org/wiki/Dolly_zoom • Continuously adjusting the focal length while the camera moves away from (or towards) the subject slide: S. Lazebnik

  18. The Dolly Zoom

  19. Facing Real Cameras • There are undesired effects in real situations • perspective distortion • Camera artifacts • aperture is not infinitely small • lens • vignetting, radial distortion • depth of field • field of view

  20. Digital camera • A digital camera replaces film with a sensor array • Each cell in the array is light-sensitive diode that converts photons to electrons • Two common types • Charge Coupled Device (CCD) • Complementary metal oxide semiconductor (CMOS) • http://electronics.howstuffworks.com/digital-camera.htm Slide by Steve Seitz

  21. Color sensing in camera: Color filter array Human Luminance Sensitivity Function Bayer grid Estimate missing components from neighboring values(demosaicing) Why more green? Source: Steve Seitz

  22. Problem with demosaicing: color moire Slide by F. Durand

  23. The cause of color moire detector Fine black and white detail in image misinterpreted as color information Slide by F. Durand

  24. Color sensing in camera: Prism • Requires three chips and precise alignment • More expensive CCD(R) CCD(G) CCD(B) slide: S. Lazebnik

  25. Color sensing in camera: Foveon X3 • CMOS sensor • Takes advantage of the fact that red, blue and green light penetrate silicon to different depths http://www.foveon.com/article.php?a=67 http://en.wikipedia.org/wiki/Foveon_X3_sensor better image quality Source: M. Pollefeys

  26. Facing Real Cameras • There are undesired effects in real situations • perspective distortion • Camera artifacts • Aperture is not infinitely small • Lens • Vignetting, radial distortion • Depth of field • Field of view • Color sensing

  27. Rolling Shutter Cameras • Many cameras use CMOS sensors (mobile, DLSR, …) • To save cost these are often rolling shutter cameras • lines are progressively exposed • line by line image reading • Rolling shutter artifacts image source: Wikipedia

  28. Rolling Shutter regular camera (global shutter) rolling shutter camera

  29. Facing Real Cameras • There are undesired effects in real situations • perspective distortion • Camera artifacts • Aperture is not infinitely small • Lens • Vignetting, radial distortion • Depth of field • Field of view • Color sensing • Rolling shutter cameras

  30. Digital camera artifacts • Noise • low light is where you most notice noise • light sensitivity (ISO) / noise tradeoff • stuck pixels • In-camera processing • oversharpening can produce halos • Compression • JPEG artifacts, blocking • Blooming • charge overflowing into neighboring pixels • Smearing • columnwiseoverexposue • Color artifacts • purple fringing from microlenses, • white balance modified from Steve Seitz

  31. Conventional versus light field camera slide: Marc Levoy

  32. Conventional versus light field camera slide: Marc Levoy

  33. Conventional versus light field camera slide: Marc Levoy

  34. Prototype camera Adaptive Optics microlens array 125μ square-sided microlenses 4000 × 4000 pixels ÷ 292 × 292 lenses = 14 × 14 pixels per lens Contax medium format camera Kodak 16-megapixel sensor slide: Marc Levoy

  35. slide: Marc Levoy

  36. Digitally stopping-down • stopping down = summing only the central portion of each microlens Σ Σ f / N light field camera, with P × P pixels under each microlens, can produce views as sharp as an f / (N × P) conventional camera slide: Marc Levoy

  37. Digital refocusing Σ • refocusing = summing windows extracted from several microlenses Σ f/N light field camera can produce views with a shallow depth of field ( f / N ) focused anywhere within the depth of field of an f / (N × P) camera images: Marc Levoy

  38. Example of digital refocusing images: Marc Levoy

  39. Extending the depth of field conventional photograph,main lens at f / 4 conventional photograph,main lens at f / 22 light field, main lens at f / 4,after all-focus algorithm[Agarwala 2004] images: Marc Levoy

  40. Digitally moving the observer • moving the observer = moving the window we extract from the microlenses Σ Σ images: Marc Levoy

  41. Example of moving the observer slide: Marc Levoy

  42. Moving backward and forward slide: Marc Levoy

  43. Historic milestones • Pinhole model:Mozi (470-390 BCE), Aristotle (384-322 BCE) • Principles of optics (including lenses):Alhacen (965-1039 CE) • Camera obscura: Leonardo da Vinci (1452-1519), Johann Zahn (1631-1707) • First photo: Joseph NicephoreNiepce (1822) • Daguerréotypes(1839) • Photographic film (Eastman, 1889) • Cinema (Lumière Brothers, 1895) • Color Photography (Lumière Brothers, 1908) • Television (Baird, Farnsworth, Zworykin, 1920s) • First consumer camera with CCDSony Mavica (1981) • First fully digital camera: Kodak DCS100 (1990) Alhacen’s notes Niepce, “La Table Servie,” 1822 CCD chip

  44. Early color photography Lantern projector • Sergey Prokudin-Gorskii (1863-1944) • Photographs of the Russian empire (1909-1916) http://en.wikipedia.org/wiki/Sergei_Mikhailovich_Prokudin-Gorskii http://www.loc.gov/exhibits/empire/

  45. First digitally scanned photograph • 1957, 176x176 pixels http://listverse.com/history/top-10-incredible-early-firsts-in-photography/