360 x 360 Mosaics Shree K. Nayar and Amruta Karmarkar Computer Science Department Columbia University IEEE CVPR Conference June 2000, Hilton Head Island,

Slides:



Advertisements
Similar presentations
DEPTH FROM DISTORTION: PERFORMING 3D RECONSTRUCTION USING A CURVED MIRROR AND SINGLE CAMERA DREXEL UNIVERSITY DEARTMENT OF MATHEMATICS ASST. PROF. ANDREW.
Advertisements

The bouncing off of light as it hits a surface
Measuring BRDFs. Why bother modeling BRDFs? Why not directly measure BRDFs? True knowledge of surface properties Accurate models for graphics.
Light Fields PROPERTIES AND APPLICATIONS. Outline  What are light fields  Acquisition of light fields  from a 3D scene  from a real world scene 
Chapters 28 Reflection and Refraction. Topics Reflection Law of Reflection – plane mirrors – diffuse reflection Refraction – Mirage Cause of Refraction.
Caustics of Catadioptric Cameras
Stereo.
Mirrors Physics 202 Professor Lee Carkner Lecture 22.
A Multicamera Setup for Generating Stereo Panoramic Video Tzavidas, S., Katsaggelos, A.K. Multimedia, IEEE Transactions on Volume: 7, Issue:5 Publication.
Vision, Video and Virtual Reality Omnidirectional Vision Lecture 6 Omnidirectional Cameras CSC 59866CD Fall 2004 Zhigang Zhu, NAC 8/203A
Steve Seitz Dept. Computer Science & Eng. University of Washington 3D Photography: Beyond Perspective.
Reflection Applets Plane Mirror Image Applets Double Mirror Images
3D Computer Vision and Video Computing Omnidirectional Vision Topic 11 of Part 3 Omnidirectional Cameras CSC I6716 Spring 2003 Zhigang Zhu, NAC 8/203A.
Announcements. Projection Today’s Readings Nalwa 2.1.
Multiple View Geometry : Computational Photography Alexei Efros, CMU, Fall 2005 © Martin Quinn …with a lot of slides stolen from Steve Seitz and.
Lecture 5: Projection CS6670: Computer Vision Noah Snavely.
Detection and Removal of Rain from Videos Department of Computer Science Columbia University Kshitiz Garg and Shree K. Nayar IEEE CVPR Conference June.
Mosaic-Based 3D Scene Representation and Rendering Zhigang Zhu Visual Computing Lab Department of Computer Science City College and Graduate Center City.
The Space of All Stereo Images Steve Seitz University of Washington.
Lecture 7: Image Alignment and Panoramas CS6670: Computer Vision Noah Snavely What’s inside your fridge?
Image Formation1 Projection Geometry Radiometry (Image Brightness) - to be discussed later in SFS.
Stereo Binocular Stereo Calibration (finish up) Next Time Motivation
Reflectance and Texture of Real-World Surfaces KRISTIN J. DANA Columbia University BRAM VAN GINNEKEN Utrecht University SHREE K. NAYAR Columbia University.
Exercise: For what purposes do we make visual representations?
Announcements Mailing list Project 1 test the turnin procedure *this week* (make sure it works) vote on best artifacts in next week’s class Project 2 groups.
Image-based Rendering of Real Objects with Complex BRDFs.
Lecture 13: Projection, Part 2
Detector lens image Traditional Camera Shree Nayar, ICIP, 2001.
Structured Light in Scattering Media Srinivasa Narasimhan Sanjeev Koppal Robotics Institute Carnegie Mellon University Sponsor: ONR Shree Nayar Bo Sun.
Chromatic Framework for Vision in Bad Weather Srinivasa G. Narasimhan and Shree K. Nayar Computer Science Department Columbia University IEEE CVPR Conference.
Surface Light Fields for 3D Photography Daniel Wood Daniel Azuma Wyvern Aldinger Brian Curless Tom Duchamp David Salesin Werner Stuetzle.
Lensless Imaging with A Controllable Aperture Assaf Zomet and Shree K. Nayar Columbia University IEEE CVPR Conference June 2006, New York, USA.
General Imaging Model Michael Grossberg and Shree Nayar CAVE Lab, Columbia University ICCV Conference Vancouver, July 2001 Partially funded by NSF ITR.
Rendering with Concentric Mosaics Heung-Yeung Shum Li-Wei he Microsoft Research.
Multiple View Geometry : Computational Photography Alexei Efros, CMU, Fall 2006 © Martin Quinn …with a lot of slides stolen from Steve Seitz and.
Measure, measure, measure: BRDF, BTF, Light Fields Lecture #6
Capturing, Modeling, Rendering 3D Structures
Depth from Diffusion Supported by ONR Changyin ZhouShree NayarOliver Cossairt Columbia University.
© 2005 Pearson Prentice Hall This work is protected by United States copyright laws and is provided solely for the use of instructors in teaching their.
Volumetric 3-Component Velocimetry (V3V)
Chapter 25 The Reflection of Light: Mirrors Wave Fronts and Rays A hemispherical view of a sound wave emitted by a pulsating sphere. The rays are.
By: Liz and Sabrina. W HAT IS A LENS ? A lens is a transparent optical device used to converge or diverge transmitted light and to form images.
Fundamental Physics II PETROVIETNAM UNIVERSITY FUNDAMENTAL SCIENCES DEPARTMENT Vungtau, 2013 Pham Hong Quang
Jitter Camera: High Resolution Video from a Low Resolution Detector Moshe Ben-Ezra, Assaf Zomet and Shree K. Nayar IEEE CVPR Conference June 2004, Washington.
Shedding Light on the Weather
Chapter 18-1 Mirrors. Plane Mirror a flat, smooth surface light is reflected by regular reflection rather than by diffuse reflection Light rays are reflected.
The Reflection of Light: Mirrors
3/4/ PHYS 1442 – Section 004 Lecture #18 Monday March 31, 2014 Dr. Andrew Brandt Chapter 23 Optics The Ray Model of Light Reflection; Image Formed.
What Does Motion Reveal About Transparency ? Moshe Ben-Ezra and Shree K. Nayar Columbia University ICCV Conference October 2003, Nice, France This work.
Metrology 1.Perspective distortion. 2.Depth is lost.
1 Finding depth. 2 Overview Depth from stereo Depth from structured light Depth from focus / defocus Laser rangefinders.
Basic Ray Tracing CMSC 435/634. Visibility Problem Rendering: converting a model to an image Visibility: deciding which objects (or parts) will appear.
1 3D Sun Loop Trace: A Tool for Stereoscopy of Coronal Loops for STEREO Jean Lorre Jeff Hall Paulett Liewer Parth Sheth Eric DeJong Jet Propulsion Laboratory.
1 Plenoptic Imaging Chong Chen Dan Schonfeld Department of Electrical and Computer Engineering University of Illinois at Chicago May
Panorama Photography and Multiperspective Imaging Szymon Rusinkiewicz, Tim Weyrich: Technology in Art and Cultural Heritage. Princeton Freshman Seminar.
December 12 th, 2001C. Geyer/K. Daniilidis GRASP Laboratory Slide 1 Structure and Motion from Uncalibrated Catadioptric Views Christopher Geyer and Kostas.
2.4 –Symmetry. Line of Symmetry: A line that folds a shape in half that is a mirror image.
Vision Sensors for Stereo and Motion Joshua Gluckman Polytechnic University.
1Ellen L. Walker 3D Vision Why? The world is 3D Not all useful information is readily available in 2D Why so hard? “Inverse problem”: one image = many.
Physics.
MIRRORS AND LENSES PAGE 59 OF INB EQ Why is distance important when discussing mirrors and lenses?
Project 2 due today Project 3 out today Announcements TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AAAAA.
Tal Amir Advanced Topics in Computer Vision May 29 th, 2015 COUPLED MOTION- LIGHTING ANALYSIS.
Auto-stereoscopic Light-Field Display By: Jesus Caban George Landon.
A light beam striking a boundary between two media can be partly transmitted and partly reflected at the boundary.
PHY 102: Lecture Wave Fronts and Rays 9.2 Reflection of Light
Date of download: 7/6/2016 Copyright © 2016 SPIE. All rights reserved. Polar plot of the magnification over the full field of view for two different panomorph.
Omnidirectional Vision
Omnidirectional Vision
Lesson 14 Key Concepts and Notes
Presentation transcript:

360 x 360 Mosaics Shree K. Nayar and Amruta Karmarkar Computer Science Department Columbia University IEEE CVPR Conference June 2000, Hilton Head Island, USA Sponsors: ONR MURI, Packard Foundation

Goal Easy Capture Process Use a Low Resolution CCD Compute a High Resolution Mosaic

Spherical Mosaics from Strips Unit Sphere : Spherical Panorama : x y z Strip Half - Strip Rotation from Correspondences: k k

Capturing 360 Degree Strips Catadioptric Imaging : Fish Eye Lens : Examples: Rees 70, Rosendahl 83, Charles 87, Nayar 88, Yagi 90, Hong 91, Powell 95, Yamazawa 95, Bogner 95, Nalwa 96, Nayar 97, Chahl & Srinivasan 97 Examples: Wood 1906, Miyamoto 64, Hall 87, Zimmerman 93, Poelstra 96, Kuban et al. 94

Resolution of a Catadioptric System ( Baker & Nayar 98 ) Resolution of Complete System Resolution of Camera + Lens image plane pixel mirror z (r) viewpoint c

Minimum Compression

Spherical Mosaic From Strips 700 pixels (8 pixels per deg.)

Spherical Mosaics from Slices Unit Sphere : Spherical Panorama : x y z Slice Half - Slice

High Resolution Slices R 1 R 2 I i Image: 500 x 500 pixels Samples On Outer Ring: 1500 Pixels Samples In 6-Pixel Disc: 4500 Pixels Increase in Samples: 3 : 1 Example: d Slice Image Samples

Deriving Sheet Cameras : Formulation viewpoint pinhole normal image plane Mirror z(r) z r parallel sheet of rays c Perspective Projection : Local Mirror Slope : Specular Reflection :

Deriving Sheet Cameras : Formulation Differential Equation : Mirror Shape :

360 Slice Cameras Image plane Hat mirror Parallel Sheet Rays Perspective Lens : Image plane Conical mirror Parallel Sheet Rays Telecentric Lens : Parabola

Variants : Folded Slice Cameras ellipsoidal mirror hat-shapped mirror camera parallel sheet paraboloid mirror conical mirror camera parallel sheet

360 Sheet Camera Rotation

360 x 360 Spherical Mosaic

Reconstruction of Step Edge edge 1 Pixel Disc 4 Pixel Disc

360 x 360 Stereo Mosaics Slice Camera Rotation : b / Slice b Left Right Left and Right Views : Stereo Panoramas: Ishiguro et al. 92, Huang and Hung 92 Peleg and Ben-Ezra 99, Shum et al. 99

Left Panorama Right Panorama

Smaller Fields of View ( Panoramas ) 0 deg. 45 deg -45 deg 640 pixels 480 pixels Increase in Resolution: 2:1

Stereoscopic Panorama

Summary 360 x 360 Spherical Mosaics Regular and Stereo High Resolution Slice Cameras Catadioptrics: Solid Angles to Image Areas