3D Reconstruction & Scanning

lbg@dongseo.ac.kr

http://graphics.stanford.edu/projects/mich/

The Digital Michelangelo Project 1997~9

Agenda

3/15/2016 lbg@dongseo.ac.kr 2

Multiple View Geometry

Depth Camera

Structured Light

Camera Calibration

Projector Calibration

http://www.ten24.info/

http://www.youtube.com/watch?v=j4waCVRgBWI

http://www.youtube.com/watch?v=Wgp0Cg3UFA4

Multiple View Geometry

in Computer Vision

2015.1

lbg@dongseo.ac.kr

http://www.cs.unc.edu/~marc/

Multiple View Geometry in Computer Vision Second Edition

Richard Hartley and Andrew Zisserman, Cambridge University Press, March 2004.

http://users.cecs.anu.edu.au/~hartley/ http://www.robots.ox.ac.uk/~vgg/index.html

M. Pollefeys, L. Van Gool, M. Vergauwen, F. Verbiest, K. Cornelis, J. Tops, R. Koch, Visual modeling with a hand-held camera, International Journal of

Computer Vision 59(3), 207-232, 2004. https://www.youtube.com/watch?feature=player_embedded&v=2mvzHvPYX0k

Visual 3D Modeling from Images

Projective Transformations

Camera Calibration

Epipolar Geometry

Feature Points

Correspondence Search

RANSAC Algorithm

3D Reconstruction

SIFT&ASIFT

Photo Tourism

http://phototour.cs.washington.edu/

https://www.youtube.com/watch?v=IgBQCoEfiMs

Building Rome on a cloudless day

Building Rome on a cloudless day, Jan-Michael Frahm, Pierre Georgel, David Gallup, Tim Johnson, Rahul Raguram, Changchang Wu, Yi-Hung Jen,

Enrique Dunn, Brian Clipp, Svetlana Lazebnik, Marc Pollefeys, ECCV 2010 https://www.youtube.com/watch?v=4cEQZreQ2zQ

Photosynth

http://photosynth.net/

https://www.youtube.com/watch?v=s-DqZ8jAmv0

Scale-invariant feature transform (or

SIFT) is an algorithm in computer vision to

detect and describe local features in images.

The algorithm was published by David Lowe in

Applications include object recognition, robotic

mapping and navigation, image stitching, 3D

modeling, gesture recognition, video tracking,

and match moving.

The algorithm is patented in the US; the owner

is the University of British Columbia.

David Lowe

Computer Science Department

University of British Columbia

2016-03-15 13

Scale Invariant Feature Transform

Depth Camera

lbg@dongseo.ac.kr

Motion sensing input device by Microsoft

Depth camera tech. developed by PrimeSense Invented in 2005

Software tech. developed by Rare

First announced at E3 2009 as “Project Natal”

Windows SDK Releases

Microsoft Kinect

http://www.microsoft.com/en-us/kinectforwindows/discover/features.aspx

lbg@dongseo.ac.kr 3/15/2016

ToF 3D Camera

Structured Light + Range Imaging

lbg@dongseo.ac.kr

http://www.cs.cmu.edu/afs/cs/academic/class/15385-s06/lectures/ppts/lec-17.ppt

http://www.sci.utah.edu/~gerig/CS6320-S2012/CS6320_3D_Computer_Vision.html

Stereo Triangulation

Correspondence is hard!

Structured Light Triangulation

Correspondence becomes easier!

Example: Laser scanner

Digital Michelangelo Project http://graphics.stanford.edu/projects/mich/

+ very accurate < 0.01 mm

− more than 10sec per scan

Cyberware® face and head scanner

Portable 3D laser scanner

http://www.youtube.com/watch?v=IqOg77liryg

Leica ScanStation C10

http://www.youtube.com/watch?v=cUI6HD_d89k

http://www.youtube.com/watch?v=1lDO1UevAJI

http://www.youtube.com/watch?v=cxTYYce_d_8

LMS LIDAR scanner from SICK

https://www.youtube.com/watch?v=yfQhEiq48YA

https://www.youtube.com/watch?v=aL-Ihvu0ugo

Structured Light 3D Surface Imaging

lbg@dongseo.ac.kr

Continuum of Triangulation Methods

Slow, robust Fast, fragile

Multi-stripe

Multi-frame

Single-frame Single-stripe

Faster Acquisition?

Project multiple stripes simultaneously

Correspondence problem: which stripe is which?

Common types of patterns:

Binary coded light striping

Gray/color coded light striping

http://vimeo.com/37090394

http://www.youtube.com/watch?v=a6g17-4FmFo

Structured Light Projection Classification

Jason Geng, "Structured-light 3D surface imaging: a tutorial," Adv. Opt. Photon. 3, 128-160 (2011)

Binary Coding

Projected

over time

Pattern 1

Pattern 2

Pattern 3

Example: 7 binary

patterns proposed

by Posdamer &

Altschuler

Codeword of this píxel: 1010010

identifies the corresponding pattern stripe

J. L. Posdamer and M. D. Altschuler. Surface measurement by space-encoded projected beam systems. Computer Graphics and Image Processing, 18:1–17, 1982.

Fringe Projection 3D Scanning

lbg@dongseo.ac.kr

Agenda

Fringe Projection Techniques

Three step phase shifting algorithm

http://www.jove.com/video/50421/high-resolution-high-speed-three-dimensional-video-imaging-with

Three-step Phase-shifting algorithm

Wrapped Phase Image

Unwrapped Phase Image

Calibration Plane

3D Result

Phase shifting patterns

Sinusoid patterns

System Setup

Large angle setting

Small angle setting

Calibration I

Calibration II

http://www.jove.com/video/50421/high-resolution-high-speed-three-dimensional-video-imaging-with

Light Field Camera

lbg@dongseo.ac.kr

Stanford Multi-Camera Array

http://graphics.stanford.edu/projects/array/

640 × 480 pixels × 30 fps × 128 cameras

synchronized timing

continuous streaming

flexible arrangement

Stanford Light Field Archive

http://lightfield.stanford.edu/lfs.html

Stanford Light Field Archive

http://lightfield.stanford.edu/lfs.html

Lytro Camera

https://www.lytro.com/

Adaptive Optics Microlens Array

Adaptive Optics microlens array

125μ square-sided microlenses

4000 × 4000 pixels ÷ 292 × 292 lenses = 14 × 14 pixels per lens

Adobe LightField Camera

http://lightfield-forum.com/light-field-camera-prototypes/adobe-lightfield-camera-protypes/

Thanks you!!

lbg@dongseo.ac.kr

http://kowon.dongseo.ac.kr/~lbg/

3D Reconstruction & Scanning

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