Presentation is loading. Please wait.

Presentation is loading. Please wait.

EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction1 Computational Plenoptic Imaging Gordon Wetzstein 1 Ivo Ihrke 2 Douglas Lanman 3 Wolfgang.

Published byAnnabella Hoover Modified over 9 years ago

Similar presentations

Presentation on theme: "EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction1 Computational Plenoptic Imaging Gordon Wetzstein 1 Ivo Ihrke 2 Douglas Lanman 3 Wolfgang."— Presentation transcript:

1 EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction1 Computational Plenoptic Imaging Gordon Wetzstein 1 Ivo Ihrke 2 Douglas Lanman 3 Wolfgang Heidrich 1 1 University of British Columbia 2 Saarland University 3 MIT Media Lab Eurographics 2011 – State of the Art Report I. Introduction

2 EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction2 The Mantis Shrimp 3 bands = trinocular vision with each eye! Up to 16 different photoreceptors: 12 for color (4 UV, visible, IR) 4 for polarization (linear & circular)

3 EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction3 Cameras are modeled as one Human Eye http://en.wikipedia.org/wiki/Bayer_filter webvision.med.utah.edu [Williams 91] How would a camera look like if it was modeled as a mantis shrimp eye?

4 EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction4 The Plenoptic Function Ray-based model for light Includes variations in space, time, wavelength, and directions [Adelson & Bergen 91] More common angular parameterization Light field is

5 EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction5 Plenoptic Information Sampled Allan Brooks, EE421, 2003 HVS Consumer Video Camera 1 continuous, ~30fps (band-limited) 3, Bayer color filter array 1920x1080 (HD) 4 Plenoptic Parameters Sampled (no V x,y,z )

6 EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction6 Computational Photography and Plenoptic Imaging CPI: joint optical modulation & computational processing of plenoptic dimensions CP: computational optics, illumination, probes, reconstruction, image processing, sensors, etc. [Raskar & Tumblin]

7 EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction7 Taxonomy and Overview II. High Dynamic Range Imaging – 10 minutes, Wetzstein III. Spectral Imaging – 10 minutes, Wetzstein IV. Light Field Acquisition – 25 minutes, Lanman V. Space & Focal Surfaces – 15 minutes, Wetzstein VI. Temporal Multiplexing – 10 minutes, Wetzstein VII. Further Light Properties – 10 minutes, Wetzstein VIII. Discussion – 5 minutes, Wetzstein

8 EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction8 Next: High Dynamic Range Imaging

Download ppt "EG 2011 | Computational Plenoptic Imaging STAR | I. Introduction1 Computational Plenoptic Imaging Gordon Wetzstein 1 Ivo Ihrke 2 Douglas Lanman 3 Wolfgang."

Similar presentations

Paul Debevec Computational Photography: Advanced Topics Computational Photography: Advanced Topics.

Paul Debevec Computational Photography: Advanced Topics Computational Photography: Advanced Topics.
R2-29 report 2004-06-08.ppt/Bp © METAS - 1 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices.

R2-29 report ppt/Bp © METAS - 1 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices.
Po-Hsiang Chen Advisor: Sheng-Jyh Wang. People  Shree K. Nayar  Ramesh Raskar  Ren Ng 2.

Po-Hsiang Chen Advisor: Sheng-Jyh Wang. People  Shree K. Nayar  Ramesh Raskar  Ren Ng 2.
Light Fields PROPERTIES AND APPLICATIONS. Outline  What are light fields  Acquisition of light fields  from a 3D scene  from a real world scene 

Light Fields PROPERTIES AND APPLICATIONS. Outline  What are light fields  Acquisition of light fields  from a 3D scene  from a real world scene 
Raskar, Camera Culture, MIT Media Lab Camera Culture Ramesh Raskar Camera Culture MIT Media Lab Ramesh Raskar

Raskar, Camera Culture, MIT Media Lab Camera Culture Ramesh Raskar Camera Culture MIT Media Lab Ramesh Raskar
Light Field Rendering Shijin Kong Lijie Heng.

Light Field Rendering Shijin Kong Lijie Heng.
Light Field Stitching with a Plenoptic Camera Zhou Xue LCAV - École Polytechnique Fédérale de Lausanne Dec. 2 2013.

Light Field Stitching with a Plenoptic Camera Zhou Xue LCAV - École Polytechnique Fédérale de Lausanne Dec
Optics in Astronomy - Interferometry - Oskar von der Lühe Kiepenheuer-Institut für Sonnenphysik Freiburg, Germany.

Optics in Astronomy - Interferometry - Oskar von der Lühe Kiepenheuer-Institut für Sonnenphysik Freiburg, Germany.
Lecture 30: Light, color, and reflectance CS4670: Computer Vision Noah Snavely.

Lecture 30: Light, color, and reflectance CS4670: Computer Vision Noah Snavely.
Capturing Light… in man and machine 15-463: Computational Photography Alexei Efros, CMU, Fall 2006 Some figures from Steve Seitz, Steve Palmer, Paul Debevec,

Capturing Light… in man and machine : Computational Photography Alexei Efros, CMU, Fall 2006 Some figures from Steve Seitz, Steve Palmer, Paul Debevec,
Computational Photography

Computational Photography
CSCE641: Computer Graphics Image Formation Jinxiang Chai.

CSCE641: Computer Graphics Image Formation Jinxiang Chai.
I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=

I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=
Lecture 20: Light, color, and reflectance CS6670: Computer Vision Noah Snavely.

Lecture 20: Light, color, and reflectance CS6670: Computer Vision Noah Snavely.
Capturing Light… in man and machine 15-463: Computational Photography Alexei Efros, CMU, Fall 2010.

Capturing Light… in man and machine : Computational Photography Alexei Efros, CMU, Fall 2010.
Computational Photography Light Field Rendering Jinxiang Chai.

Computational Photography Light Field Rendering Jinxiang Chai.
Intromission Theory: Plato, Euclid, Ptolemy, da Vinci. Plato for instance, wrote in the fourth century B. C. that light emanated from the eye, seizing.

Intromission Theory: Plato, Euclid, Ptolemy, da Vinci. Plato for instance, wrote in the fourth century B. C. that light emanated from the eye, seizing.
I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=

I.1 ii.2 iii.3 iv.4 1+1=. i.1 ii.2 iii.3 iv.4 1+1=
CSCE 641: Computer Graphics Image-based Rendering Jinxiang Chai.

CSCE 641: Computer Graphics Image-based Rendering Jinxiang Chai.
Mackenzie Mitchell BME 281 – Section 2.  Evolved for 400 million years  Highly complex  Detects circular and linear polarized light  Most animals.

Mackenzie Mitchell BME 281 – Section 2.  Evolved for 400 million years  Highly complex  Detects circular and linear polarized light  Most animals.

Similar presentations

Ads by Google