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Course 3: Computational Photography
Course 3: Computational Photography
Speaker: Jack Tumblin
Speaker: Jack Tumblin
Speaker: Ramesh Raskar
Speaker: Ramesh Raskar
Computational Photography
Computational Photography
A Teaser: Dual Photography
A Teaser: Dual Photography
A Teaser: Dual Photography
A Teaser: Dual Photography
A Teaser: Dual Photography
A Teaser: Dual Photography
A Teaser: Dual Photography
A Teaser: Dual Photography
Dual photography from diffuse reflections
Dual photography from diffuse reflections
Dual photography from diffuse reflections
Dual photography from diffuse reflections
Dual photography from diffuse reflections
Dual photography from diffuse reflections
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
A Brief History of Images
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Course 3: Computational Photography

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1Course 3: Computational Photography. 9Sensors and Computations. Generalized
Ramesh Raskar Mitsubishi Electric Research Sensor. Generalized Optics. Computations.
Labs Jack Tumblin Northwestern University. Ray Reconstruction. 4D Ray Bender. Upto 4D
Course WebPage : Ray Sampler.
http://www.merl.com/people/raskar/photo. 10Computational Photography. Novel
2Course 3: Computational Photography. Cameras. Generalized Sensor. Generalized
Course WebPage Optics. Processing.
http://www.merl.com/people/raskar/photo. 11Computational Photography. Novel
Course Evaluation Cameras. Generalized Sensor. Generalized
http://www.siggraph.org/courses_evaluation Optics. Processing. Novel Illumination.
3Welcome. Understanding Film-like Light Sources.
Photography Parameters, Nonlinearities, 12Computational Photography. Novel
Ray-based concepts Image Processing and Cameras. Generalized Sensor. Generalized
Reconstruction Tools Multi-image Fusion, Optics. Processing. Novel Illumination.
Gradient domain, Graph Cuts Improving Scene: 8D Ray Modulator. Light Sources.
Camera Performance Better dynamic range, 13Computational Photography. Novel
focus, frame rate, resolution Future Cameras. Generalized Sensor. Generalized
Directions HDR cameras, Gradient sensing, Optics. Processing. Novel Illumination.
Smart optics/lighting. Display. Scene: 8D Ray Modulator. Recreate
4Goals. Review of 30+ recent papers 4D Lightfield. Light Sources.
Understand computational aspects of 14Computational Photography. Novel
cameras Discuss issues in traditional Cameras. Generalized Sensor. Generalized
cameras Explore alternative imaging Optics. Processing. Novel Illumination. 4D
methods Learn vision and optics techniques Incident Lighting. Ray Reconstruction. 4D
Discuss image processing and Ray Bender. Upto 4D Ray Sampler. 4D Light
reconstruction tools What we will not Field. Display. Scene: 8D Ray Modulator.
cover Film Cameras, Novel view rendering Recreate 4D Lightfield. Light Sources.
(IBR), Color issues, Traditional image Modulators. Generalized Optics.
processing/editing. 15A Teaser: Dual Photography. Projector.
5Speaker: Jack Tumblin. Jack Tumblin is Photocell. Scene.
an Assistant Professor of Computer Science 16A Teaser: Dual Photography. Projector.
at Northwestern University. His interests Photocell. Scene.
include novel photographic sensors to 17A Teaser: Dual Photography. Projector.
assist museum curators in historical Photocell. Scene.
preservation, computer graphics and visual 18A Teaser: Dual Photography. Projector.
appearance, and image-based modeling and Photocell. Camera. Scene.
rendering. During his doctoral studies at 19The 4D transport matrix: Contribution
Georgia Tech and post-doc at Cornell, he of each projector pixel to each camera
investigated tone-mapping methods to pixel. projector. camera. scene.
depict high-contrast scenes. His MS in 20The 4D transport matrix: Contribution
Electrical Engineering (December 1990) and of each projector pixel to each camera
BSEE (1978), also from Georgia Tech, pixel. Sen et al, Siggraph 2005.
bracketed his work as co-founder of IVEX projector. camera. scene.
Corp., (>45 people as of 1990) where 21The 4D transport matrix: Which
his flight simulator design work was projector pixel contribute to each camera
granted 5 US Patents. He is an Associate pixel. ? Sen et al, Siggraph 2005.
Editor of ACM Transactions on Graphics, projector. camera. scene.
was a member of the SIGGRAPH Papers 22Dual photography from diffuse
Committee (2003, 2004), and in 2001 was a reflections. Sen et al, Siggraph 2005. the
Guest Editor of IEEE Computer Graphics and camera’s view.
Applications. 23A Brief History of Images. 1558.
http://www.cs.northwestern.edu/~jet. Camera Obscura, Gemma Frisius, 1558.
6Speaker: Ramesh Raskar. Ramesh Raskar 24A Brief History of Images. 1558. 1568.
is a Senior Research Scientist at MERL. Lens Based Camera Obscura, 1568.
His research interests include 25A Brief History of Images. 1558. 1568.
projector-based graphics, computational 1837. Still Life, Louis Jaques Mande
photography and non-photorealistic Daguerre, 1837.
rendering. He has published several 26A Brief History of Images. 1558. 1568.
articles on imaging and photography 1837. 1970. Silicon Image Detector, 1970.
including multi-flash photography for 27A Brief History of Images. 1558. 1568.
depth edge detection, image fusion, 1837. 1970. 1994. Digital Cameras.
gradient-domain imaging and 28Dream of A New Photography. Old New
projector-camera systems. His papers have People and Time ~Cheap Precious Each photo
appeared in SIGGRAPH, EuroGraphics, IEEE Precious Free Lighting Critical Automated*
Visualization, CVPR and many other External Sensors No Yes ‘Stills / Video’
graphics and vision conferences. He was a Disjoint Merged Exposure Settings
course organizer at Siggraph 2002, 2003 Pre-select Post-Process Exposure Time
and 2004. He is a panel organizer at the Pre-select Post-Process Resolution/noise
Symposium on Computational Photography and Pre-select Post-Process ‘HDR’ range
Video in Cambridge, MA in May 2005. He is Pre-select Post-Process.
a member of the ACM and IEEE. 29Survey. How many of you are
http://www.merl.com/people/raskar/raskar.h photographers ? How many of you are
ml. photo-artists ? How many of you are
7Opportunities. Unlocking Photography involved in camera design/development ?
How to expand camera capabilities Digital How many do active programming ? Field of
photography that goes beyond film-like work: Academics? Industry ? Research ? Art
photography Opportunities Computing ?
corrects for lens, sensor and lighting 30Schedule. 8:30 Introduction (Raskar)
limitations Computing merges results from 8:40 Photographic Signal & Film-like
multiple images Computing reconstructs Photography (Tumblin) 9:10 Image
from coded image samples Cameras benefit Processing Tools (Raskar) 9:40 Improving
from computerized light sources Think Film-like Photography (Tumblin) 10:15
beyond post-capture image processing Break 10:30 Image Reconstruction
Computation well before image processing Techniques (Raskar) 11:15 Smart Lights and
and editing Learn how to build your own Beyond Photography (Tumblin) 11:45 Smart
camera-toys. Optics and Sensors (Raskar) 12:05
8Traditional Photography. Detector. Discussion. Course Page :
Lens. Image. Pixels. http://www.merl.com/people/raskar/photo.
9Computational Photography: Optics,
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Course 3: Computational Photography

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