Classifying materials from their reflectance properties
2004 (English)In: COMPUTER VISION: ECCV 2004, PT 4, BERLIN: SPRINGER , 2004, Vol. 2034, 366-376 p.Conference paper (Refereed)
We explore the possibility of recognizing the surface material from a single image with unknown illumination, given the shape of the surface. Model-based PCA is used to create a low-dimensional basis to represent the images. Variations in the illumination create manifolds in the space spanned by this basis. These manifolds are learnt using captured illumination maps and the CUReT database. Classification of the material is done by finding the manifold closest to the point representing the image of the material. Testing on synthetic data shows that the problem is hard. The materials form groups where the materials in a group often are mis-classifed as one of the other materials in the group. With a grouping algorithm we find a grouping of the materials in the CUReT database. Tests on images of real materials in natural illumination settings show promising results.
Place, publisher, year, edition, pages
BERLIN: SPRINGER , 2004. Vol. 2034, 366-376 p.
, LECTURE NOTES IN COMPUTER SCIENCE, ISSN 0302-9743 ; 2034
illumination, surfaces, images
IdentifiersURN: urn:nbn:se:kth:diva-43994ISI: 000221523800030ScopusID: 2-s2.0-33845564200ISBN: 3-540-21981-1OAI: oai:DiVA.org:kth-43994DiVA: diva2:449131
8th European Conference on Computer Vision. Prague, CZECH REPUBLIC. MAY 11-14, 2004
QC 201110192011-10-192011-10-192011-10-19Bibliographically approved