Computational Photography: Advanced Topics. Paul Debevec
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2 Computational Photography: Advanced Topics Paul Debevec
3 Class: Computational Photography, Advanced Topics Module 1: 105 minutes Debevec,, Raskar and Tumblin 1:45: A.1 Introduction and Overview (Raskar, 15 minutes) 2:00: A.2 Concepts in Computational Photography (Tumblin,, 15 minutes) 2:15: A.3 Optics: Computable Extensions (Raskar, 30 minutes) 2:45: A.4 Sensor Innovations (Tumblin,, 30 minutes) 3:15: Q & A (15 minutes) 3:30: Break: 15 minutes Module 2: 105 minutes 3:45: B.1 Illumination As Computing (Debevec,, 25 minutes) 4:10: B.2 Scene and Performance Capture (Debevec,, 20 minutes) 4:30: B.3 Image Aggregation & Sensible Extensions (Tumblin,, 20 minutes) 4:50: B.4 Community and Social Impact (Raskar, 20 minutes) 5:10: B.4 Panel discussion (All, 20 minutes) Class Page :
4 Computational Photography: Advanced Topics B3: Image Aggregation and Sensible Extensions (20 minutes) Jack Tumblin Northwestern University
5 Image Assembly Unordered images to
6 Image Assembly Unordered images to Aligned subset to
7 Image Assembly Unordered images to Fully Aligned to
8 Image Assembly Unordered images to Fully Aligned & matched. Panoramas: thousands on Flickr autostitch
9 FUSION: Best-Focus Distance NEAR Agrawala et al., Digital Photomontage SIGGRAPH 2004
10 FUSION: Best-Focus Distance FAR Agrawala et al., Digital Photomontage SIGGRAPH 2004
11 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
12 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
13 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
14 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
15 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
16 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
17 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
18 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
19 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
20 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
21 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
22 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
23 FUSION: Best-Focus Distance Agrawala et al., Digital Photomontage SIGGRAPH 2004
24 Source images FUSION Graph Cuts Solution Agrawala et al., Digital Photomontage SIGGRAPH 2004
25 High Speed Video Say you want 120 frame per second (fps) video. You could get one camera that runs at 120 fps Or
26 High Speed Video Say you want 120 frame per second (fps) video. You could get one camera that runs at 120 fps Or get 4 cameras running at 30 fps.
27 52 Camera Cluster, 1560 FPS Levoy et al., SIGGRAPH2005
28 What else can we extend? Film-Like Camera Parameters: Field of View: image stitching for panoramas Dynamic Range: Radiance Maps Frame Rate: Interleaved Video Resolution: Super-resolution methods Visual Appearance & Content:
29 What else can we extend? Film-Like Camera Parameters: Field of View: image stitching for panoramas Dynamic Range: Radiance Maps Frame Rate: Interleaved Video [Levoy] --- DONE!! --- (mostly) Resolution: Super-resolution methods [Nayar] Visual Appearance & Available Content: Temporal Continuity: Space-time mixtures Viewpoint Constraints: Photo-Tourism, flexible collage Seam Carving & Resizing: least-loss loss deletions Learning from Large Datasets: day/night, scene elements Transfer Visible Details Multi-Light, IR relighting
30 Visually Expressive Time Fragments Duchamp Nude Descending a Staircase
31 FUSION: Time/Space Mixtures Richard Hundley 2001
32 Strip Photography (1960s, Davidhazy) Time increases left-to to-right; Girl in rotating chair
33
34 Time-Space FUSION: Shape-Time Photography Freeman et al 2003
35 Webcam Image sets: What can we learn? Archive of Many Outdoor Scenes (AMOS) Jan Hour start >500 webcams June >20 million photos Dec Date
36 Temporal Variations: VERY consistent PCA on image sets 1 st 4 components: hour-of-day 2 nd Order statistics Annotate images for: Weather, Seasons, Surface normals, Geog. Orientations
37 Temporal Variations: VERY consistent From time-stamped image sequence Find Geographic Location within 50 miles Jacobs, Pless et al; Geolocating static cameras (ICCV 20
38 Photo Tourism Photo Tourism: Exploring Photo collections In in 3D Snavely et al., SIGGRAPH 2006 Many uncalibrated photos of popular sites Each have many 3D scene point-correspondences Find, solve for 3D scene points & each camera s s 3D pose Reproject on 3D shapes, use view interpolation Friendly UI sketch-like: explore by 3D flying TRY IT!
![[SIFT, Lowe IJCV04], then Find](/docs-images/89/99614662/images/39-2.jpg "pairwise matches (refined by")
39 Feature matching Photo Tourism: Exploring Photo collections In in 3D Snavely et al., SIGGRAPH 2006 Find Features [SIFT, Lowe IJCV04], then Find pairwise matches (refined by RANSAC), then Find connected pairs components, then SfM, Image 1 Image 3 Image 2 Image 4
40 Structure from Motion Photo Tourism Photo Tourism: Exploring Photo collections In in 3D Snavely et al., SIGGRAPH 2006 p 1 p 4 p 3 p 2 p 5 p 6 p 7 minimize f(r,t,p) Camera 1 Camera 3 R 1,T 1 Camera 2 R 3,T 3 R 2,T 2
41 sd Photo Tourism Photo Tourism: Exploring Photo collections In in 3D Snavely et al., SIGGRAPH 2006
42 A tiled camera array 12 8 array of VGA cameras abutted: pixels overlapped 50%: half of this total field of view = 29 wide (seamless mosaic: not hard) cameras individually metered Approx same center-of of-proj. High performance imaging using large camera arrays Wilburn, Levoy et al.; SIGGRAPH 2005)
43 Tiled panoramic image (before) High performance imaging using large camera arrays Wilburn, Levoy SIGG 05)
44 Tiled panoramic image (after) High performance imaging using large camera arrays Wilburn, Levoy SIGG 05)
45 Scene Collage & Flexible Camera Arrays "Scene Collages and Flexible Camera Arrays," Y. Nomura, L. Zhang and S.K. Nayar, EGSR bend the camera-sheet to fit the scene Align, mix, blend photos in video collage
46 Scene Collage & Flexible Camera Arrays. "Scene Collages and Flexible Camera Arrays," Y. Nomura, L. Zhang and S.K. Nayar, EGSR 2007.
47 Multi-Light Detail Transfer SIGG2007 Fattal et al., Multiscale Shape and Detail Enhancement from Multi-light Image Collections Different light Different visible details Extract, Control/Enhance, Merge details
48 Multi-Light Detail Transfer SIGG2007 Fattal et al., Multiscale Shape and Detail Enhancement from Multi-light Image Collections Different light Different visible details Extract, Control/Enhance, Merge details Light 1
49 Multi-Light Detail Transfer SIGG2007 Fattal et al., Multiscale Shape and Detail Enhancement from Multi-light Image Collections Different light Different visible details Extract, Control/Enhance, Merge details Light 2
50 Multi-Light Detail Transfer SIGG2007 Fattal et al., Multiscale Shape and Detail Enhancement from Multi-light Image Collections Different light Different visible details Extract, Control/Enhance, Merge details Extract, Control/Enhance, Merge details Light 3
51 Multi-Light Detail Transfer SIGG2007 Fattal et al., Multiscale Shape and Detail Enhancement from Multi-light Image Collections Different light Different visible details Extract, Control/Enhance, Merge details Bilateral filters User-set set weights Adjust to suit flat, detailed or with shadows
52 Multi-Light Detail Transfer SIGG2007 Fattal et al., Multiscale Shape and Detail Enhancement from Multi-light Image Collections Different light Different visible details Extract, Control/Enhance, Merge details Bilateral filters User-set set weights Adjust to suit flat, detailed or with shadows
53 FUSION: Multispectral Wavelengths Vegetation Mapping of the Forest + = SAR Optical Landsat
54 FUSION: Multispectral Wavelengths Vegetation Mapping of the Forest + = SAR Optical Landsat
55 Bennett2007: Multispectral Video Fusion Dual-Bilateral filter: fuses best of visible + IR
56 Video Relighting from IR illumination. EG2008, Wang,Davis et al. Video Relighting Using Infrared Illumination
57 Video Relighting from IR Illumination Switched IR illuminators, 8 photos per frame Ratio Images Hue Corrections
58 Seam Carving: Content-Aware Resizing SIGG2007: Seam Carving for Content Aware Image Resizing Avidan, Shamir SEE ALSO SIGG 2008: Improved Seam Carving for Video Retargeting Rubenstien et al. Find least-damaging seam ( top bottom or left right connected path) Remove seam, or insert a similar one
59 Seam Carving: Content-Aware Resizing SIGG2007: Seam Carving for Content Aware Image Resizing Avidan, Shamir SEE ALSO SIGG 2008: Improved Seam Carving for Video Retargeting Rubenstien et al. Find least-damaging seam ( top bottom or left right connected path) Remove seam, or insert a similar one
60 Seam Carving: Content-Aware Resizing SIGG2007: Seam Carving for Content Aware Image Resizing Avidan, Shamir Find, remove least-damaging seam ( top bottom or left right connected path) SEE ALSO SIGG 2008: Improved Seam Carving for Video Retargeting Rubenstien et al.
61 Perspective? Or Not? Agrawala et al, Long Scene Panoramas, Siggraph 2006 Rademacher et al, MCOP, Siggraph 1998
62 Conclusions Merged Multiple Measurements: Multi-camera, multi-sensor, multi-optics, multi-lighting lighting Can escape obvious Optical Limits, sure lens diffraction limits, noise, available light Measurement time, position, occlusion, pose But ALSO optically impossible visual experiences Sunless shadows, Invisible lighting, wrap-around around viewpoints
63
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