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

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