dh101 2013/2014 course 4 - digitization techniques 2d and 3d

Digital Humanities 101 - 2013/2014 - Course 4

Digital Humanities Laboratory

Frederic Kaplan

frederic.kaplan@epfl.ch

About 400 persons per day on dh101.ch

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Digital Humanities 101 - 2013/2014 - Course 4 | 2013 2o

The first Venice Digital Humanities Fall Schoolhttp://digitalvenice.wordpress.com/

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Semester 1 : Content of each course

•19.09 Introduction to the course / Live Tweeting and Collective note taking

•25.09 Introduction to Digital Humanities / Wordpress / First assignment

•2.10 Introduction to the Venice Time Machine project / Zotero

•9.10 No course

•16.10 Digitization techniques / Deadline first assignment

•23.10 Transcription / XML / Presentation of projects

•30.10 Pattern recognition / OCR / Deadline peer-reviewing of first assignment

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Semester 1 : Content of each course

•6.11 Semantic modelling / RDF

•13.11 Historical Geographical Information Systems / Deadline Project selection

•20.11 Procedural modelling / City Engine

•27.11 Crowdsourcing / Wikipedia

•4.12 Group work on the projects

•11.12 New narrations and museographic experiences / Deadline Projet blog

•18.12 Oral exam / Presentation of projects

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Structure of today’s course

•2d Imaging techniques

•3d Imaging techniques

•Lot’s of material to cover but as we go, many videos and demonstrations.

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Thanks to Sabine Susstrunk for some of the materialpresented in the next slides. Check her research :http://ivrg.epfl.ch/people/susstrunk

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Image archives contain different kinds of digital images

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Images in image archives

•They are different kinds of images in an image archive.

• Images either represent digital reproduction of documents (surrogate) or are

original digital documents

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Processes that produce digital images

•Capturing images : From analog to digital

•Preserving images : Format conversion

•Displaying images : On-the-fly production of images for display

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Different usages of digital images

•Visual reference (low quality)

•Print reproduction

•Replacement of the original

•An image database typically contain one or more representations

(master/derivative files)

•The Master image is the best quality file in the archive. The Derivative image

is optimised for a specific purpose (Thumbnails, Screen reproduction, Print

reproduction)

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Digital images are produced by algorithms

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Sensors

•Type of sensors : CCD (Charge Coupled Device) and CMOS (Complementary

Metal Oxide Semiconductor)

•Photosensitive material : Silicon (semiconductor)

•Arrangement of photo cells in rows (linear arrays) and areas (area array)

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A complex process

•A colour image is the result of a complex algorithm and a particular hardware

•The resolution depends largely on the optics of the capturing system

(diffraction, lens aberrations) and only partly on the mega-pixels.

•An digital image is difficult to interpret if the information about the software

and hardware used are not provided.

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Many types of scanners exist

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Drum scanners

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ILinear arrays

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Cameras

•Cameras with colour filters for visible light

•Multispectral cameras

•Material absorption / reflectance is mostly wavelength dependent

• Imaging beyond the visible spectrum allow for surface imaging (ultra-violet)

and subsurface imaging (near and middle/far infrared)

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Multi-spectral Imaging of the Mona Lisa :http://www.dailymotion.com/video/k3GIpau9WkVvazepCB

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Capturingmethods

•You can build (almost) any capturing

technology into almost any device

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Fastest book scanner in the world : http://youtu.be/ExW64zOZGoI

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X-raymicrotomography

•Research conducted at EPFL by Prof.

Margaritando.

•Based on the advanced characteristics of

synchrotron sources, x-ray

microtomography radically transformed

the scope of standard radiology and

tomography, bringing the spatial

resolution for hard-x-rays to the record

level of 15 nm and the time resolution to

less than 1 ms per projection image.

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•Computer reconstruction of tomography

image sets yields all sorts of three

dimensional views and navigation movies

inside the specimens.

•This suggests the possibility of reading

ancient documents without even

opening or unrolling them.

•The procedure would be fully

non-invasive, fast and with a minimal

level of risk.

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•The practical testing and

implementation requires a targeted effort

to solve a number of problems and to

realize a field implementation right

where the patrimony is located i.e.,

without a synchrotron source.

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Formats

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Compression

•No compression is appropriate for all master files and files that will be

re-processed extensively.

•Lossless compression (LZW, JPEG2000). Same as above. The size of the file

is usually around 0.5 to 0.7 of the uncompressed file size

•Lossy compression (JPEG, JPEG2000, GIF, PNG) : Derivative encoding for

storage and transmission.

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File formats

•For master files, the file format should be a standard.

•TIFF, EXIF, JPX(JPEG2000) are standard file formats.

•Derivative files can be encoded depending on the application

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Metadata

• Image metadata (camera and scene parameter) facilate rendering a sensor

encoded image to an output-referred image. TIFF, EXIF, JPX have defined

mandatory and optional tags.

•Metadata tags are also used to store copyright information

• Image metadata should always be stored with the image file.

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3d digitization techniques

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Demo 123DCatch

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Thanks to Roberto Scopigno for some of the materialpresented in the next slides. Check his researchhttp://http://vcg.isti.cnr.it/~scopigno/

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Families of 3d digitization techniques

•2D image-based rendering (panoramic images, RTI images)

•Standard CAD modelling (manual process)•Approaches based on Sampling• 3d scanning (active)

• 3d from images (passive)

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2D image-based rendering : Panoramic images

•Some image-based rendering are interesting for some applications

• If you don’t have to move in your model, panoramic images can be enough.

•Ex : Cluny Augmented Reality System :

http://www.youtube.com/watch?v=Z-EwXWjU0nw

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2D image-based rendering : RTI

•RTI stands for Reflection Transmission Images. his is done by putting your

camera on a tripod by taking several images and regularly changing the light.

•Sometimes a dome is used http://vimeo.com/67164689

•With such images, you cannot change the view, but change the way your

image reflects light. For instance, you can move a virtual light and see how it

affects your image.

•Ex : RTI example : papyrus fragment from Cultural Heritage Imaging :

http://vimeo.com/33245119

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Modelling approaches and sampling approaches

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Modelling approaches and sampling approaches

•There are big differences in terms of approaches between modelling

approaches and sampling approaches.

•Modelling implies redrawing. Before photography, painters where making

drawings of other painters painting. With the arrival of photography one could

start sampling the painting.

•The same olds for 3d models. You have wonderful technology developed for

the movie market that permits to produce great 3d models. The 3D model is

usually complete. On the contrary, sampling/scanning approaches the 3D

model, accuracy is known is usually uncompleted (many unstapled regions). If

you want to communicate, 3D models are great, if you want to study a

building, sampling is interesting.

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3d scanning devices

•There are different 3d scanning devices.

•They use active optical technologies. You need for instance a laser and a

camera.

•The regions that are not seen by the two devices cause problem in the

restitution.

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3d scanning devices : Triangulation

•Triangulation is an old an simple approach (Thales)

•Such systems are good for small/medium scale artefacts (e.g. statues). They

permit to reach high accuracy (0.05 mm) and a very dense sampling, very

rapidly (300 000 points / s)

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3d scanning devices : Time of Flight techniques

•Time of Flight techniques measure the time a light impulse needs to travel

form the emitter to the target point.

•A source emits a light pulse and starts a nanosecond watch.

•With Time of flight techniques, one can do large scale models (architectures).

This can work in wide workspace, but accuracy is smaller. This because sound

is too slow and light is too fast.

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Kinect

•Kinect is of less good quality than these techniques. But it has a better

framerate.

• If you have application where the dynamic acquisition is important.

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Material extracted from

•http://www.iuav.it/SISTEMA-DE/Laboratori2/laboratori/pubblicazi/2011_asita-Canal-Grande.pdf

•http://www.iuav.it/SISTEMA-DE/Laboratori2/laboratori/pubblicazi/2008_laser-scanner.pdf

•http://www.iuav.it/SISTEMA-DE/Laboratori2/laboratori/pubblicazi/2012-Archeomatica.pdf

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3d scanning pipeline

•Planning (where are you going to put your scanners)

•Acquisition

•Editing (removing people, etc.)

•Registration (aligning coordinate systems of different scans, 4 points are

enough)

•Merging (Based on a set of range map, a single surface is computed, this is

typically done by another software using for instance Poisson surface

reconstruction),

•Simplification (for using on a webpage or for 3d printing), texturing.

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Merging

• In some sense, merging is destroying the data, creating an medium shape.

•Actually, some architects prefer to use point clouds directly obtained based on

sampling.

•But it is also a way of improving the accuracy of the model, removing the

noise thought this smoothing process.

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Multiresolution encoding

•Multiresolution encoding can be build on top of simplification technology.

•The goal is to structure the data to allow to extract from the model (in real

time) an optimal representation for the current view (view dependent models

produced on the fly).

•This is particularly interesting if you are rendering terrains. Mesh is more and

more coarse as we get farther from viewpoint. Zones which are outside the

view frustum are very coarse.

•For multiresolution encoding, you have to keep all the intermediate levels of

simplification. Some de facto standards exist for terrain (used in Google

Earth). For object there is no de facto standard.

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Assisted modelling

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SketchUp

•You can start with a single image and use SketchUp

(http://sketchup.com)

• If this image permits to extract the main lines of perspective you can model

rapidly the 3d shape of an object.

•You need to find some features of the object that permits to have two axis

(ideally orthogonal).

•You draw the two vanishing lines.

•Partial calibration with only a single photo is sufficient provided only the axis

can be recovered.

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Demo Sketchup

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Photogrammetry

•For photogrammetry you need several images and click on points which are

common to the different images.

•These points permits to estimate the camera position for the different images.

•For simple geometry you can get very good reconstruction in very short time.

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Multi-view stereomatching algorithms

• In the recent years a new class of algorithms has tried to completely

automatised these processes. These are multi-view stereo matching algorithms.

• In some sense the approach is the inverse of assisted learning. You can have a

very large number of point (with a lot of errors). You remove the errors and

wait to have a good number of points.

•You need to take pictures close to one another, so that the computer can

match them easily.

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One interesting example of the use of such algorithms isthe Photo Tourism project using photo by tourists(phototour.cs.washington.edu/).

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Demo 123DCatch

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Sketchup vs 123DCatch ?

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Sketchup vs 123DCatch ?

•For multi-view stereo matching algorithms to work you need many features on

the objects.

•Assisted modelling approach using for instance SketchUp can work for non

textured objects.

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What we have not covered

•3d Printing

•Documenting the material

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