CS395/495: Spring 2004 IBMR: Image Based Modeling in addition to Rendering Admin: How this course works GOAL: First-Class Primitive

CS395/495: Spring 2004 IBMR: Image Based Modeling in addition to Rendering Admin: How this course works GOAL: First-Class Primitive www.phwiki.com

CS395/495: Spring 2004 IBMR: Image Based Modeling in addition to Rendering Admin: How this course works GOAL: First-Class Primitive

Burrough, DJ, Freelance Journalist has reference to this Academic Journal, PHwiki organized this Journal CS395/495: Spring 2004 IBMR: Image Based Modeling in addition to Rendering Introduction Jack Tumblin jet@cs.northwestern.edu Admin: How this course works Refer to class website: (soon) http://www.cs.northwestern.edu/~jet/Teach/2004-3spr-IBMR/IBMRsyllabus2004.htm Tasks: Reading, lectures, class participation, projects Evaluation: Progressive Programming Project Take-Home Midterm In-class project demo; no final exam GOAL: First-Class Primitive Want images as ‘first-class’ primitives Useful as BOTH input in addition to output Convert to/from traditional scene descriptions Want to mix real & synthetic scenes freely Want to extend photography Easily capture scene: shape, movement, surface/BRDF, lighting Modify & Render the captured scene data -BUT- images hold only PARTIAL scene in as long as mation “You can’t always get what you want” –(Mick Jagger 1968)

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Back To Basics: Scene & Image Light + 3D Scene: Illumination, shape, movement, surface BRDF, Image Plane I(x,y) Angle(,) Position(x,y) 2D Image: Collection of rays through a point Trad. Computer Graphics Light + 3D Scene: Illumination, shape, movement, surface BRDF, Image Plane I(x,y) Angle(,) Position(x,y) 2D Image: Collection of rays through a point Reduced, Incomplete In as long as mation Trad. Computer Vision Light + 3D Scene: Illumination, shape, movement, surface BRDF, !TOUGH! ‘ILL-POSED’ Many Simplifications, External knowledge Image Plane I(x,y) Angle(,) Position(x,y) 2D Image: Collection of rays through a point

IBMR Goal: Bidirectional Rendering Both as long as ward in addition to ‘inverse’ rendering! 2D Display Image(s) Camera Pose Camera View Geom Scene illumination Object shape, position Surface reflectance, transparency 2D Display Image(s) 2D Display Image(s) 2D Display Image(s) IBMR Traditional Computer Graphics ‘3D Scene’ Description ‘Optical’ Description ! New Research OLDEST IBR: Shadow Maps (1984) Fast Shadows from Z-buffer hardware: 1) Make the “Shadow Map”: Render image seen from light source, BUT Keep ONLY the Z-buffer values (depth) 2) Render Scene from Eyepoint: Pixel + Z depth gives 3D position of surface; Project 3D position into Shadow map image If Shadow Map depth < 3D depth, SHADOW! Early IBR: QuickTime VR (Chen, Williams ’93) 1) Four Planar Images 1 Cylindrical Panorama: Re-sampling Required! Planar Pixels: equal distance on x,y plane (tan-1) Cylinder Pixs: horiz: equal angle on cylinder () vert: equal distance on y (tan-1) Early IBR: QuickTime VR (Chen, Williams ’93) 1) Four Planar Images 1 Cylindrical Panorama: IN: OUT: Early IBR: QuickTime VR (Chen, Williams ’93) 2) Windowing, Horizontal-only Reprojection: IN: OUT: Early IBR: QuickTime VR (Chen, Williams ’93) 2) Windowing, Horizontal-only Reprojection: IN: OUT: View Interpolation: How But what if no depth is available Traditional Stereo Disparity Map: pixel-by-pixel search as long as correspondence View Interpolation: How Store Depth at each pixel: reproject Coarse or Simple 3D model: Plenoptic Array: ‘The Matrix Effect’ Brute as long as ce! Simple arc, line, or ring array of cameras Synchronized shutter http://www.ruffy.com/firingline.html Warp/blend between images to change viewpoint on ‘time-frozen’ scene: as long as a given scene, describe ALL rays through ALL pixels, of ALL cameras, at ALL wavelengths, ALL time F(x,y,z, ,, , t) “Eyeballs Everywhere” function (5-D x 2-D!) Plenoptic Function (Adelson, Bergen `91) Seitz: ‘View Morphing’ SIGG`96 http://www.cs.washington.edu/homes/seitz/vmorph/vmorph.htm 1)Manually set some corresp.points (eye corners, etc.) 2) pre-warp in addition to post-warp to match points in 3D, 3) Reproject as long as Virtual cameras Seitz: ‘View Morphing’ SIGG`96 http://www.cs.washington.edu/homes/seitz/vmorph/vmorph.htm Seitz: ‘View Morphing’ SIGG`96 http://www.cs.washington.edu/homes/seitz/vmorph/vmorph.htm Seitz: ‘View Morphing’ SIGG`96 http://www.cs.washington.edu/homes/seitz/vmorph/vmorph.htm Seitz: ‘View Morphing’ SIGG`96 http://www.cs.washington.edu/homes/seitz/vmorph/vmorph.htm ‘Scene’ causes Light Field Light field: holds all outgoing light rays Shape, Position, Movement, BRDF, Texture, Scattering Emitted Light Reflected, Scattered, Light Cameras capture subset of these rays. Can we recover Shape Can you find ray intersections Or ray depth Ray colors might not match as long as non-diffuse materials (BRDF) Can we recover Surface Material Can you find ray intersections Or ray depth Ray colors might not match as long as non-diffuse materials (BRDF) Burrough, DJ Burrough, DJ Freelance Journalist www.phwiki.com

Hey, wait Light field describes light LEAVING the enclosing surface . Isn’t there a complementary ‘light field’ as long as the light ENTERING the surface YES ‘Image-Based Lighting’ too! Cleaner Formulation: Orthographic camera, positioned on sphere around object/scene Orthographic projector, positioned on sphere around object/scene F(xc,yc,c,c,xl,yl l,l, , t) ‘Full 8-D Light Field’ (10-D, actually: time, ) camera Cleaner Formulation: Orthographic camera, positioned on sphere around object/scene Orthographic projector, positioned on sphere around object/scene F(xc,yc,c,c,xl,yl l,l, , t) ‘Full 8-D Light Field’ (10-D, actually: time, ) camera c c

Cleaner Formulation: Orthographic camera, positioned on sphere around object/scene Orthographic projector, positioned on sphere around object/scene F(xc,yc,c,c,xl,yl l,l, , t) ‘Full 8-D Light Field’ (10-D, actually: time, ) camera Projector (laser brick) Cleaner Formulation: Orthographic camera, positioned on sphere around object/scene Orthographic projector, positioned on sphere around object/scene ( in addition to wavelength in addition to time) F(xc,yc,c,c,xl,yl l,l, , t) ‘Full 8-D Light Field’ (10-D, actually: time, ) camera projector Cleaner Formulation: Orthographic camera, positioned on sphere around object/scene Orthographic projector, positioned on sphere around object/scene ( in addition to wavelength in addition to time) F(xc,yc,c,c,xl,yl l,l, , t) ‘Full 8-D Light Field’ (10-D, actually: time, ) camera projector

Conclusion Heavy overlap with computer vision: careful not to re-invent & re-name! Elegant Geometry is at the heart of it all, even surface reflectance, illumination, etc. etc. THUS: we’ll dive into geometry-all the rest is built on it!

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