03/10/2013

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3D from images, an overview

9th October 2013

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Perspective and Stereo

We do perceive the environment three-dimensionality

thanks to our stereo vision AND the perspective

projection that occurs in our eyes..

Using the geometric laws of this two phenomena

we can build the 3D geometry of the scene

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Perspective Camera

All starts here... a camera is defined by parameters:

- Position

- Orientation

- Focal Length

- Viewport

Distortion

Given a point in 3D space, it is know the projected point on

photo plane

Given a point in the photo, it is possible to trace back the

ray which originated the pixel

2 paths...

Two possible directions

- Assisted Modeling

- Automatic Stereo Matching

The underlying principles are the same... but they sprouted

different kind of tools...

I'll cover the first, Matteo will take over later on

As usual, this distinction is becoming blurry...

...things does converge, after all

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ASSISTED MODELING

Assisted Modeling

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Sketchup

A very strange modeling tool.

Follows more the way a technical drawing is done on paper

(reporting/referencing) than the usual 3D modeling metaphore.

Easier for people with a technical drawing/sketching background.

Easier for people with no experience in 3D modeling.

Focused towards modeling of buildings

and mechanical entities...

Acquired by Google some years ago...

distributed now as a semi-free tool

http://sketchup.google.com/

Sketchup – the Luni Temple

An ideal tool for very regular buildings... like this one

(regular does not equal new)

http://sketchup.google.com/

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Sketchup Photo Match

Assited modeling from a SINGLE photo

Calibration: axis and vanishing points markup

Modeling: 3D drawing by axis/reference reporting

Partial calibration, with only a single photo, only the axis can be recovered.

SketchUp can be used to model by reporting/referencing

Example 1 – Example 2

Photogrammetry

Perspective & stereo

Common reference points are marked on

multiple images…

From these correspondences it is

possible to calculate camera

position/parameters and 3D

location of the marked

points

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ImageModeler

Photogrammetry commercial tool

Points are marked on input images, camera are fully calibrated using these

points, camera are calibrated and modeling can be done using the

recovered 3D points

Acquired by Autodesk... now it costs

three times the old price (with the same features)

PhotoModeler

Photogrammetry commercial tool

The tool for the professionals... Two steps: camera calibration (with markers

and references) and camera pose estimation. Modeling and measuring with lots of different tools

Very, very, very complex to use...

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MULTI-VIEW STEREO MATCHING

1 - Automatic matching of images

The entire process is based on finding matches between images.

Record your pictures not too far apart, so the computer can match them easily!

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2 - Camera Calibration

No prior knowledge about camera calibration is available, so all information must be recovered from the images

It is therefore important that enough information is present in the images!

Important factors:

Motion of the camera

General structure of the scene

Enough overlap (only points that are visible in at least 3 images are useful)

What you want reconstruct and how you get the photos have great influence on the final reconstruction (!!)

Calibrated Cameras: what you can do with them

Photo Tourism

Having a set of (even etherogeneous) images, you can navigate the photo collection in a “spatially coherent” way. It evolved into PhotoSynth (see later).

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3 - Dense Matching

After recovery of the camera calibration, dense depth maps are computed

These contain the depth of every pixel and a quality measure (how confident we are of each particular pixel)

Depth Map

Photosynth Toolkit

The Photosynth toolkit is the result of the work of people from a Blog (Visual Experiments)

The code of Bundler (SIFT+Camera Calibration) has been made available recently

In alternative, it’s possible to use the Photosynth service

Moreover, further code for the surface reconstruction (CMVS -> PMVS)

The Toolkit is available and works locally

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Photosynth Toolkit

Also the Photosynth toolkit can be integrated with MeshLab, so that the final result can be improved!

SfMToolkit

It’s the same toolkit as PhotosynthToolkit, but it’s completely local

http://www.visual-experiments.com/demos/sfmtoolkit/

Good: completely local, no upload, control on parameters

Bad: completely local, sometimes it crashes…

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Python Photogrammetry Toolbox

Developed by Arc-Team, open source and free, for Debian and Win (32 and 64bit)

http://www.arc-team.com/

Good: completely local, interface, control on parameters, video tutorial

Bad: completely local, a bit tricky to install…

Autodesk 123Dcatch

Very well engineered tool...

Works on a remote server, like Arc3D

Produces a complete, textured model

http://www.123dapp.com/catch

It is free (for now), and works very very well.

It is fast, works on difficult datasets and the results looks good. However, not really high resolution, and there is less control over the process. It is a good tool to start with...

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Autodesk 123Dcatch

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PhotoScan

Commercial, low cost tool: 59 € for educational license, 179€ standard license. (win, mac & linux)

Fast, work on local machine, directly produce textured model. Very robust and reliable... We have used it with good results on many diverse datasets.

They also have a free tool to process images taken with stereo (two lenses) cameras....

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PhotoModeler - dense

Photogrammetry commercial tool, 2nd version

The tool is the same as before... after doing the camera calibration, instead

of using only user-picked points, the system does a dense-matching.

The result is quite similar to a range map... you need to do standard

processing in order to obtain a 3D model...

Model creation with MeshLab

After the 3D model is exported in MeshLab, there’s a procedure to enhance it a bit and have a final result:

Cleaning

Sampling

Poisson reconstruction

Poisson Model cleaning

Vertex Color Transfer

Cleaning

Scaling

Saving!

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Conclusion

The methods for the acquisition of 3D content from images have become an interesting alternative to 3D scanning.

Probably they won’t take the place of 3D Scanning, but they could be a valid solution in a number of practical and professional applications.

Nowadays, they are already used in archeologists everyday work, and they are undergoing a sort of standardization process.

Knowing these yechnologies is key to be able to deal with 3D and CH.

Wanna know more?

Check the webpage of my University course:

http://vcg.isti.cnr.it/~dellepiane/Corso.html

(page in italian, slides mostly in English)

You’ll find slides, datasets, links etc etc

Do you want to learn how to use MeshLab?

Start from Mister P. Video tutorials

http://www.youtube.com/user/MrPMeshLabTutorials

Several playlists available