Research output per year
Research output per year
Carlos Hernández*, George Vogiatzis
Research output: Chapter in Book/Published conference output › Chapter
Acquiring 3D shape from images is a classic problem in Computer Vision occupying researchers for at least 20 years. Only recently however have these ideas matured enough to provide highly accurate results. We present a complete algorithm to reconstruct 3D objects from images using the stereo correspondence cue. The technique can be described as a pipeline of four basic building blocks: camera calibration, image segmentation, photo-consistency estimation from images, and surface extraction from photo-consistency. In this Chapter we will put more emphasis on the latter two: namely how to extract geometric information from a set of photographs without explicit camera visibility, and how to combine different geometry estimates in an optimal way.
Original language | English |
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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 | 281-311 |
Number of pages | 31 |
ISBN (Electronic) | 978-3-642-12848-6 |
ISBN (Print) | 978-3-642-12847-9 |
DOIs | |
Publication status | Published - 2010 |
Name | Studies in Computational Intelligence |
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Publisher | Springer |
Volume | 285 |
ISSN (Print) | 1860-949X |
Research output: Chapter in Book/Published conference output › Chapter