Abstract
Photometric Stereo is a powerful image based 3D reconstruction technique that has recently been used to obtain very high quality reconstructions. However, in its classic form, Photometric Stereo suffers from two main limitations: Firstly, one needs to obtain images of the 3D scene under multiple different illuminations. As a result the 3D scene needs to remain static during illumination changes, which prohibits the reconstruction of deforming objects. Secondly, the images obtained must be from a single viewpoint. This leads to depth-map based 2.5 reconstructions, instead of full 3D surfaces. The aim of this Chapter is to show how these limitations can be alleviated, leading to the derivation of two practical 3D acquisition systems: The first one, based on the powerful Coloured Light Photometric Stereo method can be used to reconstruct moving objects such as cloth or human faces. The second, permits the complete 3D reconstruction of challenging objects such as porcelain vases. In addition to algorithmic details, the Chapter pays attention to practical issues such as setup calibration, detection and correction of self and cast shadows. We provide several evaluation experiments as well as reconstruction results.
| Original language | English |
|---|---|
| Title of host publication | Computer vision |
| Subtitle of host publication | detection, recognition and reconstruction |
| Editors | Roberto Cipolla, Sebastiano Battiato, Giovanni Maria Farinella |
| Place of Publication | Berlin (US) |
| Publisher | Springer |
| Pages | 313-345 |
| Number of pages | 33 |
| ISBN (Electronic) | 978-3-642-12848-6 |
| ISBN (Print) | 978-3-642-12847-9 |
| DOIs | |
| Publication status | Published - 2010 |
Publication series
| Name | Studies in Computational Intelligence |
|---|---|
| Publisher | Springer |
| Volume | 285 |
| ISSN (Print) | 1860-949X |
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Practical 3D reconstruction based on photometric stereo. / Vogiatzis, George; Hernández, Carlos.
Computer vision: detection, recognition and reconstruction. ed. / Roberto Cipolla; Sebastiano Battiato; Giovanni Maria Farinella. Berlin (US) : Springer, 2010. p. 313-345 (Studies in Computational Intelligence; Vol. 285).Research output: Chapter in Book/Report/Conference proceeding › Chapter
TY - CHAP
T1 - Practical 3D reconstruction based on photometric stereo
AU - Vogiatzis, George
AU - Hernández, Carlos
PY - 2010
Y1 - 2010
N2 - Photometric Stereo is a powerful image based 3D reconstruction technique that has recently been used to obtain very high quality reconstructions. However, in its classic form, Photometric Stereo suffers from two main limitations: Firstly, one needs to obtain images of the 3D scene under multiple different illuminations. As a result the 3D scene needs to remain static during illumination changes, which prohibits the reconstruction of deforming objects. Secondly, the images obtained must be from a single viewpoint. This leads to depth-map based 2.5 reconstructions, instead of full 3D surfaces. The aim of this Chapter is to show how these limitations can be alleviated, leading to the derivation of two practical 3D acquisition systems: The first one, based on the powerful Coloured Light Photometric Stereo method can be used to reconstruct moving objects such as cloth or human faces. The second, permits the complete 3D reconstruction of challenging objects such as porcelain vases. In addition to algorithmic details, the Chapter pays attention to practical issues such as setup calibration, detection and correction of self and cast shadows. We provide several evaluation experiments as well as reconstruction results.
AB - Photometric Stereo is a powerful image based 3D reconstruction technique that has recently been used to obtain very high quality reconstructions. However, in its classic form, Photometric Stereo suffers from two main limitations: Firstly, one needs to obtain images of the 3D scene under multiple different illuminations. As a result the 3D scene needs to remain static during illumination changes, which prohibits the reconstruction of deforming objects. Secondly, the images obtained must be from a single viewpoint. This leads to depth-map based 2.5 reconstructions, instead of full 3D surfaces. The aim of this Chapter is to show how these limitations can be alleviated, leading to the derivation of two practical 3D acquisition systems: The first one, based on the powerful Coloured Light Photometric Stereo method can be used to reconstruct moving objects such as cloth or human faces. The second, permits the complete 3D reconstruction of challenging objects such as porcelain vases. In addition to algorithmic details, the Chapter pays attention to practical issues such as setup calibration, detection and correction of self and cast shadows. We provide several evaluation experiments as well as reconstruction results.
UR - http://www.scopus.com/inward/record.url?scp=77950638820&partnerID=8YFLogxK
UR - http://link.springer.com/chapter/10.1007%2F978-3-642-12848-6_12
U2 - 10.1007/978-3-642-12848-6_12
DO - 10.1007/978-3-642-12848-6_12
M3 - Chapter
AN - SCOPUS:77950638820
SN - 978-3-642-12847-9
T3 - Studies in Computational Intelligence
SP - 313
EP - 345
BT - Computer vision
A2 - Cipolla, Roberto
A2 - Battiato, Sebastiano
A2 - Farinella, Giovanni Maria
PB - Springer
CY - Berlin (US)
ER -