Multi-perspective Panoramas

Slides:



Advertisements
Similar presentations
Recognising Panoramas M. Brown and D. Lowe, University of British Columbia.
Advertisements

Generating Classic Mosaics with Graph Cuts Y. Liu, O. Veksler and O. Juan University of Western Ontario, Canada Ecole Centrale de Paris, France.
Image Registration  Mapping of Evolution. Registration Goals Assume the correspondences are known Find such f() and g() such that the images are best.
Character Animation from 2D Pictures and 3D Motion Data ACM Transactions on Graphics 2007.
Constructing immersive virtual space for HAI with photos Shingo Mori Yoshimasa Ohmoto Toyoaki Nishida Graduate School of Informatics Kyoto University GrC2011.
Announcements Project 2 Out today Sign up for a panorama kit ASAP! –best slots (weekend) go quickly...
Multi-perspective Panoramas Slides from a talk by Lihi Zelnik-Manor at ICCV’07 3DRR workshop.
Recognising Panoramas
Direct Methods for Visual Scene Reconstruction Paper by Richard Szeliski & Sing Bing Kang Presented by Kristin Branson November 7, 2002.
Lecture 7: Image Alignment and Panoramas CS6670: Computer Vision Noah Snavely What’s inside your fridge?
Automatic Panoramic Image Stitching using Local Features Matthew Brown and David Lowe, University of British Columbia.
Lecture 11: Structure from motion CS6670: Computer Vision Noah Snavely.
Image Stitching and Panoramas
Automatic Image Stitching using Invariant Features Matthew Brown and David Lowe, University of British Columbia.
Lecture 13: Projection, Part 2
1Jana Kosecka, CS 223b Cylindrical panoramas Cylindrical panoramas with some slides from R. Szeliski, S. Seitz, D. Lowe, A. Efros,
CSCE 641 Computer Graphics: Image Mosaicing Jinxiang Chai.
CS664 Lecture #19: Layers, RANSAC, panoramas, epipolar geometry Some material taken from:  David Lowe, UBC  Jiri Matas, CMP Prague
Panorama Stitching and Augmented Reality. Local feature matching with large datasets n Examples: l Identify all panoramas and objects in an image set.
Announcements Project 1 artifact voting Project 2 out today (help session at end of class)
Announcements Midterm due Friday, beginning of lecture Guest lecture on Friday: Antonio Criminisi, Microsoft Research.
Light Field Video Stabilization ICCV 2009, Kyoto Presentation for CS 534: Computational Photography Friday, April 22, 2011 Brandon M. Smith Li Zhang University.
Mosaics CSE 455, Winter 2010 February 8, 2010 Neel Joshi, CSE 455, Winter Announcements  The Midterm went out Friday  See to the class.
Single-view modeling, Part 2 CS4670/5670: Computer Vision Noah Snavely.
Photocollage System. What is Photocollage? Photographic approach in combining multiple images to create a new whole Result is an expressive composition.
Automatic Registration of Color Images to 3D Geometry Computer Graphics International 2009 Yunzhen Li and Kok-Lim Low School of Computing National University.
Image Stitching Shangliang Jiang Kate Harrison. What is image stitching?
MESA LAB Multi-view image stitching Guimei Zhang MESA LAB MESA (Mechatronics, Embedded Systems and Automation) LAB School of Engineering, University of.
Image-based rendering Michael F. Cohen Microsoft Research.
Mosaics Today’s Readings Szeliski, Ch 5.1, 8.1 StreetView.
Image stitching Digital Visual Effects Yung-Yu Chuang with slides by Richard Szeliski, Steve Seitz, Matthew Brown and Vaclav Hlavac.
Yu-Wing Tai, Hao Du, Michael S. Brown, Stephen Lin CVPR’08 (Longer Version in Revision at IEEE Trans PAMI) Google Search: Video Deblurring Spatially Varying.
Panorama Photography and Multiperspective Imaging Szymon Rusinkiewicz, Tim Weyrich: Technology in Art and Cultural Heritage. Princeton Freshman Seminar.
MSRI workshop, January 2005 Object Recognition Collected databases of objects on uniform background (no occlusions, no clutter) Mostly focus on viewpoint.
Scene Reconstruction Seminar presented by Anton Jigalin Advanced Topics in Computer Vision ( )
Smoothly Varying Affine Stitching [CVPR 2011]
The Lit Sphere: A Model for Capturing NPR Shading from Art Peter-Pike Sloan, William Martin, Amy Gooch & Bruce Gooch.
ELE 488 Fall 2006 Image Processing and Transmission ( )
Visualizing the Cosmos: Smoke or Mirrors? Designing Visualization Imagery David Bock National Center for Supercomputing Applications University of Illinois,
Photo-Quality Enhancement based on Visual Aesthetics S. Bhattacharya*, R. Sukthankar**, M.Shah* *University of Central Florida, **Intel labs & CMU.
3D Visual Phrases for Landmark Recognition
CS 4501: Introduction to Computer Vision Sparse Feature Detectors: Harris Corner, Difference of Gaussian Connelly Barnes Slides from Jason Lawrence, Fei.
Cubism Photomontage.
Nearest-neighbor matching to feature database
COSC579: Image Align, Mosaic, Stitch
Scene Modeling for a Single View
Image-Based Rendering
Multi-Perspective Panoramas
Fast Preprocessing for Robust Face Sketch Synthesis
CENG 477 Introduction to Computer Graphics
Interactive Computer Graphics
© 2005 University of Wisconsin
Image Stitching Slides from Rick Szeliski, Steve Seitz, Derek Hoiem, Ira Kemelmacher, Ali Farhadi.
Features Readings All is Vanity, by C. Allan Gilbert,
Nearest-neighbor matching to feature database
Representing Moving Images with Layers
Image Based Modeling and Rendering (PI: Malik)
Announcements Project 2 out today (help session at end of class)
“The Truth About Cats And Dogs”
Structure from Motion with Non-linear Least Squares
Image Stitching Computer Vision CS 678
Noah Snavely.
David Hockney Painter Photographer Artist. David Hockney Painter Photographer Artist.
Announcements Project 1 artifact voting Project 2 out today
Computational Photography
Calibration and homographies
Lecture 15: Structure from motion
Occlusion and smoothness probabilities in 3D cluttered scenes
Image Registration  Mapping of Evolution
Structure from Motion with Non-linear Least Squares
Presentation transcript:

Multi-perspective Panoramas Slides from a talk by Lihi Zelnik-Manor at ICCV’07 3DRR workshop

Panoramas Registration: Brown & Lowe, ICCV’05 Blending: Burt & Adelson, Trans. Graphics,1983 Visualization: Kopf et al., SIGGRAPH, 2007

Output of Brown & Lowe software Bad panorama? Output of Brown & Lowe software

No geometrically consistent solution

Scientists solution to panoramas: Single center of projection No 3D!!! Registration: Brown & Lowe, ICCV’05 Blending: Burt & Adelson, Trans. Graphics,1983 Visualization: Kopf et al., SIGGRAPH, 2007

From sphere to plane Distortions are unavoidable

Output of Brown & Lowe software Distorted panoramas Actual appearance Output of Brown & Lowe software

Objectives Better looking panoramas Let the camera move: Any view Natural photographing

Stand on the shoulders of giants Cartographers Artists

Cartographic projections

Common panorama projections Perspective Stereographic θ φ Cylindircal

Global Projections Perspective Stereographic Cylindircal

Learn from the artists Sharp discontinuity Multiple view points perspective Sharp discontinuity Multiple view points De Chirico “Mystery and Melancholy of a Street”, 1914

Two horizons!

Renaissance painters solution “School of Athens”, Raffaello Sanzio ~1510 Give a separate treatment to different parts of the scene!!

Personalized projections “School of Athens”, Raffaello Sanzio ~1510 Give a separate treatment to different parts of the scene!!

Multiple planes of projection Sharp discontinuities can often be well hidden

Single view Our multi-view result

Single view Our multi-view result

Single view Our multi-view result

Applying personalized projections Input images Foreground Background panorama

Single view Our multi-view result

Single view Our multi-view result

Objectives - revisited Better looking panoramas Let the camera move: Any view Natural photographing Multiple views can live together

Multi-view compositions 3D!! David Hockney, Place Furstenberg, (1985)

Why multi-view? Multiple viewpoints Single viewpoint David Hockney, Place Furstenberg, 1985 Melissa Slemin, Place Furstenberg, 2003

Multi-view panoramas Requires video input Single view Multiview Zomet et al. (PAMI’03) Requires video input

Long Imaging Agarwala et al. (SIGGRAPH 2006)

Smooth Multi-View Google maps

What’s wrong in the picture? Google maps

Non-smooth Google maps

The Chair David Hockney (1985)

Joiners are popular Flickr statistics (Aug’07): 4,985 photos matching joiners. 4,007 photos matching Hockney. 41 groups about Hockney Thousands of members

Main goals: Automate joiners Generalize panoramas to general image collections

Objectives For Artists: Reduce manual labor Manual: ~40min. Fully automatic

Objectives For Artists: Reduce manual labor For non-artists: Generate pleasing-to-the-eye joiners

Objectives For Artists: Reduce manual labor For non-artists: Generate pleasing-to-the-eye joiners For data exploration: Organize images spatially

What’s going on here?

A cacti garden

Principles

Principles Convey topology Correct Incorrect

Principles Convey topology A 2D layering of images Blending: blurry Graph-cut: cuts hood Desired joiner

Principles Convey topology A 2D layering of images Don’t distort images translate rotate scale

Principles Convey topology A 2D layering of images Don’t distort images Minimize inconsistencies Bad Good

Algorithm

Step 1: Feature matching Brown & Lowe, ICCV’03

Large inconsistencies Step 2: Align Large inconsistencies Brown & Lowe, ICCV’03

Reduced inconsistencies Step 3: Order Reduced inconsistencies

Ordering images Try all orders: only for small datasets

Ordering images Try all orders: only for small datasets complexity: (m+n) m = # images n = # overlaps  = # acyclic orders

Ordering images Observations: Typically each image overlaps with only a few others Many decisions can be taken locally

Ordering images Approximate solution: Solve for each image independently Iterate over all images

Can we do better?

Step 4: Improve alignment

Iterate Align-Order-Importance

Iterative refinement Initial Final

Iterative refinement Initial Final

Iterative refinement Initial Final

What is this?

That’s me reading

Anza-Borrego

Tractor

Art reproduction Paolo Uccello, 1436

Art reproduction Paolo Uccello, 1436 Zelnik & Perona, 2006

Art reproduction Single view-point Zelnik & Perona, 2006

Manual by Photographer

Our automatic result

Failure?

GUI

The Impossible Bridge

Homage to David Hockney

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.

Thank You

15-463 Class Project from 2007 http://www.cs.cmu.edu/afs/andrew/scs/cs/15-463/f07/proj_final/www/echuangs/