Multi-perspective Panoramas. Slides from a talk by Lihi Zelnik-Manor at ICCV 07 3DRR workshop
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1 Multi-perspective Panoramas Slides from a talk by Lihi Zelnik-Manor at ICCV 07 3DRR workshop
2 Objectives 1. Better looking panoramas 2. Let the camera move: Any view Natural photographing
3 Stand on the shoulders of giants Cartographers Artists
4 Cartographic projections
5 Common panorama projections Perspective Stereographic Cylindircal φ θ
6 Global Projections Perspective Stereographic Cylindircal
7 Learn from the artists Multiple view points Sharp discontinuity perspective perspective De Chirico Mystery and Melancholy of a Street, 1914
8 Renaissance painters solution School of Athens, Raffaello Sanzio ~1510 Give a separate treatment to different parts of the scene!!
9 Personalized projections School of Athens, Raffaello Sanzio ~1510 Give a separate treatment to different parts of the scene!!
10 Multiple planes of projection Sharp discontinuities can often be well hidden
11 Single view Our multi-view result
12 Single view Our multi-view result
13 Single view Our multi-view result
14 Input images Applying personalized projections Foreground Background panorama
15 Single view Our multi-view result
16 Objectives - revisited 1. Better looking panoramas 2. Let the camera move: Any view Natural photographing Multiple views can live together
17 Multi-view compositions David Hockney, Place Furstenberg, (1985)
18 Why multi-view? Multiple viewpoints Single viewpoint David Hockney, Place Furstenberg, 1985 Melissa Slemin, Place Furstenberg, 2003
19 Long Imaging Agarwala et al. (SIGGRAPH 2006)
20 Smooth Multi-View Google maps
21 What s wrong in the picture? Google maps
22 Non-smooth Google maps
23 The Chair David Hockney (1985)
24 Joiners are popular Flickr statistics (Aug 07): 4,985 photos matching joiners. 4,007 photos matching Hockney. 41 groups about Hockney Thousands of members
25 Main goals: Automate joiners Generalize panoramas to general image collections
26 For Artists: Reduce manual labor Objectives Manual: ~40min. Fully automatic
27 For Artists: Reduce manual labor Objectives For non-artists: Generate pleasing-to-the-eye joiners
28 For Artists: Reduce manual labor Objectives For non-artists: Generate pleasing-to-the-eye joiners For data exploration: Organize images spatially
29 What s going on here?
30 A cacti garden
31 Principles
32 Principles Convey topology Correct Incorrect
33 Principles Convey topology A 2D layering of images Blending: blurry Graph-cut: cuts hood Desired joiner
34 Principles Convey topology A 2D layering of images Don t distort images translate rotate scale
35 Principles Convey topology A 2D layering of images Don t distort images Minimize inconsistencies Bad Good
36 Algorithm
37 Step 1: Feature matching Brown & Lowe, ICCV 03
38 Step 2: Align Large inconsistencies Brown & Lowe, ICCV 03
39 Step 3: Order Reduced inconsistencies
40 Ordering images Try all orders: only for small datasets
41 Ordering images Try all orders: only for small datasets complexity: (m+n)α m = # images n = # overlaps α = # acyclic orders
42 Ordering images Observations: Typically each image overlaps with only a few others Many decisions can be taken locally
43 Ordering images Approximate solution: Solve for each image independently Iterate over all images
44 Can we do better?
45 Step 4: Improve alignment
46 Iterate Align-Order-Importance
47 Iterative refinement Initial Final
48 Iterative refinement Initial Final
49 Iterative refinement Initial Final
50 What is this?
51 That s me reading
52 Anza-Borrego
53 Tractor
54 Paolo Uccello, 1436 Art reproduction
55 Art reproduction Paolo Uccello, 1436 Zelnik & Perona, 2006
56 Art reproduction Single view-point Zelnik & Perona, 2006
57 Manual by Photographer
58 Our automatic result
59 Failure?
60 GUI
61 The Impossible Bridge
62 Homage to David Hockney
63 Take home Incorrect geometries are possible and fun! Geometry is not enough, we need scene analysis A highly related work: "Scene Collages and Flexible Camera Arrays, Y. Nomura, L. Zhang and S.K. Nayar, Eurographics Symposium on Rendering, Jun, 2007.
64 Thank You
65 Class Project from /f07/proj_final/www/echuangs/
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