Abstract
We describe a new stereoscopic system based on a multispectral camera and an LCD-Projector. The novel concept we want to show consists in the use of multispectral information for 3D-scenes reconstruction. Each 3D point is linked to a curve representing the spectral reflectance. This latter is a physical representation of the matter and presents the advantage over color information, which is perceptual, that it is independent from both illuminant and observer. We first present an easy methodology to geometrically and spectrally calibrate such a system. We then describe an algorithm for recovering 3D coordinates based on triangulation and an algorithm for reflectance curves reconstruction based on neural networks. The results are encouraging. they confirm the feasibility of such a system and in the same time enable some multimedia applications like simulating illumination change.
Keywords
- Multispectral Image
- Geometrical Calibration
- Stereoscopic System
- Multispectral Imaging System
- Luminous Pattern
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
Battle, J., Mouaddib, J., Salvi, J.: Recent Progress in Coded Structured Light as a Technique to Solve the Correspondence Problem: a Survey. Pattern recognition 31(7), 963–982 (1998)
Rusinkiewicz, S., All-Holt, O., Levoy, M.: Real-Time 3D Model Acquisition. In: ACM Trans. On Graphics, Siggraph 2002 (2002)
Jaeggli, T., Koninckx, T.P., Van Gool, L.: Online 3D Acquisition and Model Integration. In: IEEE international workshop on projector-camera systems (in conjunction with ICCV 2003), France (October 2003)
Hardeberg, J.Y.: Acquisition and reproduction of colour images: colorimetric and multispectral approaches, dissertation.com, Parkland, Florida, USA (2001)
Mansouri, A., Marzani, F.S., Hardeberg, J.Y., Gouton, P.: Optical calibration of a multispectral imaging system based on interference filters. Optical Engineering 44(2) (February 2005)
Tominaga, S.: Spectral imaging by multichannel camera. Journal of Electronic Imaging 8(4) (October 1999)
Woo, S., Dipanda, A., Marzani, F., Voisin, Y.: Determination of an optimal configuration for a direct correspondance in an active stereovision system. In: Proc. of 2nd IASTED INT. Conf. VIIP Espagne, pp. 596–601 (2002)
Lathuiliere, A., Marzani, F.S., Voisin, Y.: Modélisation d’un projecteur vidéo suivant le modéle du sténopé dans le cadre d’un systéme de stéréovision active. In: Proc. of 4éme colloque francophone, Contrôles et Mesures Optique pour l’Industrie, France, novembre 17-21, pp. 27–32 (2003)
Mansouri, A., Marzani, F.S., Gouton, P.: Development of a protocol for CCD calibration: application to a multispectral imaging system. International Journal of Robotics and Automation 20(2), 94–100 (2005)
Mansouri, A., Sanchez, M., Marzani, F.S., Gouton, P.: Spectral Reflectance Estimation From Multispectral Images using Neural Networks. In: Proc. of Physics in Signal and Image Processing (PSIP), Toulouse, France (January 2005)
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© 2005 Springer-Verlag Berlin Heidelberg
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Mansouri, A., Lathuiliere, A., Marzani, F.S., Voisin, Y., Gouton, P. (2005). A Neural Network-Based Algorithm for 3D Multispectral Scanning Applied to Multimedia. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_78
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DOI: https://doi.org/10.1007/11559573_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29069-8
Online ISBN: 978-3-540-31938-2
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