3D MULTISPECTRAL
ACQUISITION
Steven Le Moan, Alamin Mansouri
Université de Bourgogne, Auxerre, FR
Workshop on Multispectral imaging and Biometrics
Gjøvik University College – November 2010
OUTLINE
Context & goals
 3D multispectral scanner
 Depth imaging
 Space carving
 Perspectives

CONTEXT & GOALS

How to describe a real-life object ?
Shape, color, touch, smell, sound,..

How does it look like ?
Shape + Color >> 3D multispectral
CONTEXT & GOALS

What is a 3D multispectral dataset ?
Way too many dimensions !
One “pixel” is defined by:
- 3 spatial coordinates (X,Y,Z)
- N spectral values (B1, B2, ..., BN)
>> Multimodal (N+3) dimensional space
3D MULTISPECTRAL SCANNER

System overview
Mansouri A., Etude, conception et réalisation d’un système multispectral de vision pour des applications de
proximité et développement d’algorithmes de reconstruction de la reflectance, PhD Thesis, 2005
3D MULTISPECTRAL SCANNER

Calibration
Caltech Calibration Toolbox for Matlab
3D MULTISPECTRAL SCANNER

Acquisition
3D MULTISPECTRAL SCANNER

Results
3D MULTISPECTRAL SCANNER

Results
3D MULTISPECTRAL SCANNER
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Limitations (to be improved)
- Lack of convenience
- Heavy calibration
- What about pearlescence ?
DEPTH IMAGING

Principle
The depth is printed in the blanket.
Page D., Part decomposition of 3D surfaces, PhD thesis, 2003
DEPTH IMAGING

-
LIDAR (LIght Detection And Ranging)
Remote sensing applications
Short wavelengths (UV – nIR)
Time-of-flight cameras
- Close-range applications (up to 60m)
- “One shot” acquisition

DEPTH IMAGING

Examples
Roy M., Comparaison et analyse multirésolution de maillages irréguliers avec attributs d’apparence, PhD Thesis, 2004
DEPTH IMAGING

Examples
Image provided by Norsk Elektro Optikk
SPACE CARVING

Reconstruction from a set of images
PERSPECTIVES

Convenience (“point & shoot”)

Fast calibration

Unified framework ?
THANK YOU FOR YOUR ATTENTION