Practical 3D reconstruction based on photometric stereo

George Vogiatzis*, Carlos Hernández

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputChapter


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 languageEnglish
Title of host publicationComputer vision
Subtitle of host publicationdetection, recognition and reconstruction
EditorsRoberto Cipolla, Sebastiano Battiato, Giovanni Maria Farinella
Place of PublicationBerlin (US)
Number of pages33
ISBN (Electronic)978-3-642-12848-6
ISBN (Print)978-3-642-12847-9
Publication statusPublished - 2010

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X


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  • Shape from photographs: a multi-view stereo pipeline

    Hernández, C. & Vogiatzis, G., 2010, Computer vision: detection, recognition and reconstruction. Cipolla, R., Battiato, S. & Farinella, G. M. (eds.). Berlin (US): Springer, p. 281-311 31 p. (Studies in Computational Intelligence; vol. 285).

    Research output: Chapter in Book/Published conference outputChapter

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