Po-Hsiang Chen Advisor: Sheng-Jyh Wang. People  Shree K. Nayar  Ramesh Raskar  Ren Ng 2.

Slides:



Advertisements
Similar presentations
Exposure Basics Introduction to Photography. What is Exposure  In photography, exposure is the total amount of light allowed to fall on the digital sensor.
Advertisements

Fast Separation of Direct and Global Images Using High Frequency Illumination Shree K. Nayar Gurunandan G. Krishnan Columbia University SIGGRAPH Conference.
Procam and Campro Shree K. Nayar Computer Science Columbia University Support: NSF, ONR Procams 2006 PROCAMS Shree K. Nayar,
IITB-Monash Research Academy An Indian-Australian Research Partnership IIT Bombay Projection Defocus Correction using Adaptive Kernel Sampling and Geometric.
1 Michael M. Bronstein New dimensions of media 1 November 2007 New dimensions of media Michael M. Bronstein Department of Computer Science Technion – Israel.
Light Fields PROPERTIES AND APPLICATIONS. Outline  What are light fields  Acquisition of light fields  from a 3D scene  from a real world scene 
Structured light and active ranging techniques Class 11.
Vision Sensing. Multi-View Stereo for Community Photo Collections Michael Goesele, et al, ICCV 2007 Venus de Milo.
Raskar, Camera Culture, MIT Media Lab Camera Culture Ramesh Raskar Camera Culture MIT Media Lab Ramesh Raskar
Light field photography and videography Marc Levoy Computer Science Department Stanford University.
SIGGRAPH Course 30: Performance-Driven Facial Animation Section: Markerless Face Capture and Automatic Model Construction Part 2: Li Zhang, Columbia University.
Structured light and active ranging techniques Class 8.
Computational Photography
Image or Object? Michael F. Cohen Microsoft Research.
Detector lens image Traditional Camera Shree Nayar, ICIP, 2001.
Lensless Imaging with A Controllable Aperture Assaf Zomet and Shree K. Nayar Columbia University IEEE CVPR Conference June 2006, New York, USA.
Graphics research and courses at Stanford
 Marc Levoy Synthetic aperture confocal imaging Marc Levoy Billy Chen Vaibhav Vaish Mark Horowitz Ian McDowall Mark Bolas.
CSCE 641: Computer Graphics Image-based Rendering Jinxiang Chai.
 Marc Levoy IBM / IBR “The study of image-based modeling and rendering is the study of sampled representations of geometry.”
 Marc Levoy IBM / IBR “The study of image-based modeling and rendering is the study of sampled representations of geometry.”
Lecture 33: Computational photography CS4670: Computer Vision Noah Snavely.
Light field photography and microscopy Marc Levoy Computer Science Department Stanford University.
Dinesh Ganotra. each of the two eyes sees a scene from a slightly different perspective.
Course 3: Computational Photography Ramesh Raskar Mitsubishi Electric Research Labs Jack Tumblin Northwestern University Course WebPage :
Northeastern University, Fall 2005 CSG242: Computational Photography Ramesh Raskar Mitsubishi Electric Research Labs Northeastern University Course WebPage.
The University of Ontario CS 4487/9587 Algorithms for Image Analysis n Web page: Announcements, assignments, code samples/libraries,
Course 15: Computational Photography Organisers Ramesh Raskar Mitsubishi Electric Research Labs Jack Tumblin Northwestern University Course WebPage :
Light Field. Modeling a desktop Image Based Rendering  Fast Realistic Rendering without 3D models.
Light field photography and videography Marc Levoy Computer Science Department Stanford University.
Northeastern University, Fall 2005 CSG242: Computational Photography Ramesh Raskar Mitsubishi Electric Research Labs Northeastern University September.
Light Field Video Stabilization ICCV 2009, Kyoto Presentation for CS 534: Computational Photography Friday, April 22, 2011 Brandon M. Smith Li Zhang University.
Stereoscopic 3D 2013/10/30. Stereoscopic Image Transforms to Autostereoscopic Multiplexed Image Wei-Ming Chen, Chi-Hao Chiou and Sheng-Hao Jhang Computer.
OUTLINEOUTLINE What is Photography? What is Photography? What is ‘The Photographic Signal’? What is ‘The Photographic Signal’? Perfecting Film-Like Photography:
3D/Multview Video. Outline Introduction 3D Perception and HVS 3D Displays 3D Video Representation Compression.
MERL, MIT Media Lab Reinterpretable Imager Agrawal, Veeraraghavan & Raskar Amit Agrawal, Ashok Veeraraghavan and Ramesh Raskar Mitsubishi Electric Research.
Structured light and active ranging techniques Class 8
Computational Photography and Videography Christian Theobalt and Ivo Ihrke Winter term 09/10.
Digital Photography A tool for Graphic Design Graphic Design: Digital Photography.
Introduction to Computational Photography. Computational Photography Digital Camera What is Computational Photography? Second breakthrough by IT First.
Advanced Computer Graphics (Spring 2013) CS 283, Lecture 15: Image-Based Rendering and Light Fields Ravi Ramamoorthi
KinectFusion : Real-Time Dense Surface Mapping and Tracking IEEE International Symposium on Mixed and Augmented Reality 2011 Science and Technology Proceedings.
Dynamically Reparameterized Light Fields Aaron Isaksen, Leonard McMillan (MIT), Steven Gortler (Harvard) Siggraph 2000 Presented by Orion Sky Lawlor cs497yzy.
Computational photography CS4670: Computer Vision Noah Snavely.
A Case Study using the Hugh Morton Photograph Collection A Photographic Journey brought to you by the Digital Production Center.
Nonphotorealistic rendering, and future cameras Computational Photography, Bill Freeman Fredo Durand May 11, 2006.
. Wild Dreams for Cameras Jack Tumblin Northwestern University From May 24 Panel Discussion on cameras.
1 Finding depth. 2 Overview Depth from stereo Depth from structured light Depth from focus / defocus Laser rangefinders.
Image Based Rendering. Light Field Gershun in 1936 –An illuminated objects fills the surrounding space with light reflected of its surface, establishing.
Interreflections : The Inverse Problem Lecture #12 Thanks to Shree Nayar, Seitz et al, Levoy et al, David Kriegman.
EG 2011 | Computational Plenoptic Imaging STAR | VI. High Speed Imaging1 Computational Plenoptic Imaging Gordon Wetzstein 1 Ivo Ihrke 2 Douglas Lanman.
 Marc Levoy  Light Field = Array of (virtual) Cameras Sub-aperture Virtual Camera = Sub-aperture View.
Raskar, Camera Culture, MIT Media Lab Camera Culture Ramesh Raskar Camera Culture MIT Media Lab Ramesh Raskar.
Immersive Rendering. General Idea ► Head pose determines eye position  Why not track the eyes? ► Eye position determines perspective point ► Eye properties.
 Marc Levoy Using Plane + Parallax to Calibrate Dense Camera Arrays Vaibhav Vaish, Bennett Wilburn, Neel Joshi, Marc Levoy Computer Science Department.
Transparent Object Reconstruction via Coded Transport of Intensity Supplemental Video Paper ID: 846.
EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction1 Computational Plenoptic Imaging Gordon Wetzstein 1 Ivo Ihrke 2 Douglas Lanman 3 Wolfgang.
{ Photography technique.  Perspective refers to the relationship of imaged objects in a photograph. This includes their relative positions and sizes.
Camera surface reference images desired ray ‘closest’ ray focal surface ‘closest’ camera Light Field Parameterization We take a non-traditional approach.
Auto-stereoscopic Light-Field Display By: Jesus Caban George Landon.
Advanced Science and Technology Letters Vol.46 (Games and Graphics 2014), pp On Study of the Volumetric.
Introduction Computational Photography Seminar: EECS 395/495
Aperture and Depth of Field
A tool for Graphic Design
What I Need To Know About Operating A Camera
Sampling and Reconstruction of Visual Appearance
Rob Fergus Computer Vision
Macroscopic Interferometry with Electrons, not Photons
Experiments can be reproduced using off-the-shelf ToF cameras
A tool for Graphic Design
Presentation transcript:

Po-Hsiang Chen Advisor: Sheng-Jyh Wang

People  Shree K. Nayar  Ramesh Raskar  Ren Ng 2

Light Field 3 Levoy, M. (2006). "Light fields and computational imaging." Computer 39(8): D representation4D representation

Computational Photography  Extend the capabilities of digital photography 4

App: Light Field Rendering 5

App: Synthetic Aperture Photography 6

7

App: Wave-front Coding 8 Object Lens CCD Wave-front Coding Optical Element 曾禎宇,” [090204]Wavefront_coding,” Vision Lab, NCTU Levin, A., R. Fergus, et al. (2007). "Image and depth from a conventional camera with a coded aperture." ACM Transactions on Graphics (TOG) 26(3): 70-es.

9

What we are interesting in … 10

App: Dual Photography 11 standard photograph from camera dual photograph from projector Sen, P., B. Chen, et al. (2005). "Dual photography." ACM Transactions on Graphics (TOG) 24(3):

Helmholtz reciprocity 12 scene projector photosensor primal

Helmholtz reciprocity 13 projector photosensor projector photosensor scene light camera dual

14

15 C’ shrinks to 1x1 scalar T shrinks to 1xpq vector Result Dual photo Scanning through the projector

Flying spot scanner 16

Adaptive Multiplexed Illumination 17

Scene relighting 18 Camera Array?

19

App: Looking Around the Corner 20 Kirmani, A., T. Hutchison, et al. (2009). “Looking around the corner using transient imaging.” ICCV2009, CVPR2011

21

Transient Light Transport  Scene S with M small planar P i  Z i defines the 3D position  D ij defines the distances between Ps 22

Space Time Impulse Response 23

Distance from STIR 24

Structure from Pairwise Distance  Isometric embedding 25 Dattorro, J. (2005). "Convex optimization & Euclidean distance geometry", Meboo Publishing USA.

Scenes with Occluders 26

27

28

29

30

3D displays: Stereoscopic  Disparity 31

Anaglyph image 32

Polarized glasses 33

Shutter glasses 34

Glass-free: Parallax barrier 35

Glass-free: Holography 36 Schnars, U. and W. Jueptner (2005). "Digital holography", Springer.

37 Slinger, C., C. Cameron, et al. (2005). "Computer-generated holography as a generic display technology." Computer 38(8):

App: Layered 3D 38 Wetzstein, G., D. Lanman, et al. (2011). “Layered 3D: tomographic image synthesis for attenuation-based light field and high dynamic range displays,” ACM, Siggraph 2011.

Tomographic Image Synthesis 39

40 Prototype multi-layer display

41