Back to Search
Start Over
Solving Uncalibrated Photometric Stereo using Total Variation
- Source :
- Journal of Mathematical Imaging and Vision, Journal of Mathematical Imaging and Vision, Springer Verlag, 2015, vol. 52 (n° 1), pp. 87-107. ⟨10.1007/s10851-014-0512-5⟩
- Publication Year :
- 2015
- Publisher :
- Springer-Verlag, 2015.
-
Abstract
- International audience; Estimating the shape and appearance of an object, given one or several images, is still an open and challenging research problem called 3D-reconstruction. Among the different techniques available, photometric stereo (PS) produces highly accurate results when the lighting conditions have been identified. When these conditions are unknown, the problem becomes the so-called uncalibrated PS problem, which is ill-posed. In this paper, we will show how total variation can be used to reduce the ambiguities of uncalibrated PS, and we will study two methods for estimating the parameters of the generalized bas-relief ambiguity. These methods will be evaluated through the 3D-reconstruction of real-world objects.
- Subjects :
- Statistics and Probability
Computer science
Photometric stereo
media_common.quotation_subject
Generalized bas-relief ambiguity
Variation (game tree)
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Traitement des images
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing
Traitement du signal et de l'image
Computer vision
Synthèse d'image et réalité virtuelle
media_common
Total variation
3D-reconstruction
business.industry
Applied Mathematics
[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
Ambiguity
Vision par ordinateur et reconnaissance de formes
Intelligence artificielle
Condensed Matter Physics
Object (computer science)
[INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR]
Modeling and Simulation
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
Geometry and Topology
Computer Vision and Pattern Recognition
Artificial intelligence
business
Subjects
Details
- Language :
- English
- ISSN :
- 09249907 and 15737683
- Database :
- OpenAIRE
- Journal :
- Journal of Mathematical Imaging and Vision
- Accession number :
- edsair.doi.dedup.....00b58436a395d98e356c0ec79c10debf
- Full Text :
- https://doi.org/10.1007/s10851-014-0512-5⟩