Course Topic What is Computational Photography ? Study the basics - - PDF document

Computational Photography

CS 4475/6475 Maria Hybinette

1 Maria Hybinette

Course Topic

• What is “Computational Photography”?
• Study the basics of computation and its impact on the entire

workflow of photography, from

– capturing, – manipulating, and – collaborating on, and – sharing photographs.

• Focus is on the computational pipeline not how to use the

camera – but we will do some usage too…

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Where are the Algorithms?

• Using ‘computations’ to create an image.
• Using ‘computations’ to extend the hardware

– On camera – Off-camera

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Who am I

• Photography: Started out with interest in the

‘artistic’ form of photography and expanded studying the computational aspect in 2005-2006

– Felt understanding the science helps understanding the ‘art’ at a deeper level – Sold photographs a number of photographs through Getty Images (both Stock and Creative photographs, their categories). – More of a hobby now but occasional use flickr

• https://www.flickr.com/photos/cooriander/
• Academics: Emory University
• Graduated from G-Tech in 1995, and 2000
• Teaches at the University of Georgia

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Today

• Tomorrow :

– Deeper Dive into computational photography – 2 examples putting computational photography in context

• Dual photography
• Panorama

– Python/OpenCV discussion setup.

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• Overview of the materials that we will cover in the

course

• Expected background
• and what to except from the course

Learning Tools & Evaluated

• Again it is about the

computations in the photography

– Learn via hands-on experimentation

• Frequent Homework

Assignments (almost weekly)

– Coding mostly

• 3 mini projects through the

summer

– Free form

• Quizzes 3

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Communication Links

• Piazza
• T Square
• Schedule Page

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h"p://cobweb.cs.uga.edu/~maria/classes/2016-CompPhoto/schedule.html

Expected Background & Platforms

• Math Knowledge

– Linear Algebra (matrices, vectors) – Calculus (differential and integration) – Probability (sampling, and distributions functions)

• Computation

– Python (easy to pick up) – OpenCV (CV = computer vision)

• Hardware

– Laptop – Fancy Camera (not required), but you will need access to some image generating device

• Control: Exposure, Color, Focus, and Lenses (Length)

– Images will be provided in most cases.

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Theme: Computational Photography

• Buildings the computational technology and tools

how to figure out :

• How light is used to produce images and

photographs.

– Rays to Images (pixels) – Images to Sharing

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Wk1: Introduction

• What is computational

photography?

• Computational Photography

as a discipline

• 2 practical Examples of

Computational Photography providing context.

• Assignment

– Sharing pictures both the good and the bad – Getting set up. Python, OpenCV

Maria Hybinette 10 h"p://graphics.cs.cmu.edu/?page_id=16

Wk 2-3: Image Processing and Analysis

• Digital Image Representation
• Pixel/Point processes for

images

• Smoothing and filtering

methods for Images

• Extracting features from

Images

• Assignments: Experiments

with Image Filtering, Features Detection

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Wk 4: Camera, Optics & Sensors

• Digital Image

Representation Pixel/Point Processes for Images

• Smoothing and Filtering

methods for Images

• Extracting Features from

Images

• Assignments:

Experiments with Image Filtering, Features Detection

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Wk 5: Image Blending/Merging

• Sampling and

Frequencies

• Image Blending
• Homework: Exercise on

Image Blending

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Wk 6-X: More Advanced Concepts

• More advanced concepts
• Feature Detection
• Panoramas
• HDR
• Image Editing.

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Computational Photography Combines

• Computing
• Digital Sensors
• Modern Optics
• Actuators – control aspects of photography
• Smart Lights
• To “escape”the limitations of traditional

film cameras

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Limitations of Photography

• Blur, camera shake, noise, damage

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h"p://www.cs.unc.edu/~lazebnik/research/fall08/

Limitations of Photography

• Limited Resolution

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Limitations of Photography

• Bad color / monochromatic

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h"p://learningdslr.com/2010/10/colour-temperature-white-balance/ h"p://en.wikipedia.org/wiki/Black-and-white

Limitations of Photography

• Unwanted objects

Maria Hybinette 19 h"p://www.glosonblog.com/adobe-photoshop-how-to-remove- unwanted-items-from-photos/ h"p://cpn.canon-europe.com/content/educaIon/technical/ photoshop_cs3_2.do

Limitations of Photography

• Limited dynamic range

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h"p://en.wikipedia.org/wiki/High_dynamic_range_imaging

Limitations of Photography

• Single depth of focus

Maria Hybinette 21 h"p://www.janrik.net/insects/ExtendedDOF/LepSocNewsFinal/EDOF_NewsLepSoc_2005summer.htm

Elements of Computational Photography

• Computation can be embedded in all aspects of

these elements to support photography rays to pixels to sharing.

• Enhance the photographic process

– Rays to pixels

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Source: Irfan Essa

Sources & Inspiration

Contributors of Course Material:

• Marc Levoy (Stanford)– taught computational

photography since 2002: – A leader in the field : Frankecamera

• Irfan Essa & Frank Dellaert (Georgia Tech)

– Also early adopters – Field Trip, Guest Lecturer (HDR)

• Frédo Durand (MIT)
• Jack Tumblin (Northwestern)
• Wikipedia
• http://www.all-art.org/

history658_photography1.html

• “Photography”, London, Stone, Upton

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Tomorrow

• Deeper dive into computational

photography

• 2 examples putting computational

photography in context – Dual photography – Panorama

• Computational photography and how

it relates to other disciplines.

• Python/OpenCV discussion setup.

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Computational Photography

Study the basics of the impact of computation on the entire workflow of photography, from how images are captured, manipulated and collaborated on, and shared.

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