Joint Estimation of Shape and Reflectance using Multiple Images with Known Illumination Conditions

Kuk-Jin Yoon 1 Emmanuel Prados 1 Peter Sturm 1
1 PERCEPTION - Interpretation and Modelling of Images and Videos
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : We propose a generative model based method for recovering both the shape and the reflectance of the surface(s) of a scene from multiple images, assuming that illumination conditions and cameras calibration are known in advance. Based on a variational framework and via gradient descents, the algorithm minimizes simultaneously and consistently a global cost functional with respect to both shape and reflectance. Contrary to previous work which considers and specializes in a specific scenario, our method applies indiscriminately with a number of classical scenarios; in particular it works for classical stereovision, multiview photometric stereo and multiview shape from shading. Moreover, unlike most previous methods dealing with only Lambertian surfaces, the proposed method considers general dichromatic surfaces. We verify the method using synthetic and real data sets containing specular reflection.
Document type :
Journal articles
Complete list of metadatas

Cited literature [43 references]  Display  Hide  Download

https://hal.inria.fr/inria-00266293
Contributor : Emmanuel Prados <>
Submitted on : Friday, March 21, 2008 - 3:31:44 PM
Last modification on : Wednesday, May 30, 2018 - 12:21:58 PM
Long-term archiving on : Friday, September 28, 2012 - 11:40:25 AM

File

ijcv_mvstereo.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Kuk-Jin Yoon, Emmanuel Prados, Peter Sturm. Joint Estimation of Shape and Reflectance using Multiple Images with Known Illumination Conditions. International Journal of Computer Vision, Springer Verlag, 2010, 86 (2-3), pp.192-210. ⟨http://springerlink.metapress.com/content/m82880786g283vhr/⟩. ⟨10.1007/s11263-009-0222-4⟩. ⟨inria-00266293⟩

Share

Metrics

Record views

477

Files downloads

424