DocumentCode
2115327
Title
Can similar scenes help surface layout estimation?
Author
Divvala, Santosh K. ; Efros, Alexei A. ; Hebert, Martial
Author_Institution
Robot. Inst., Carnegie Mellon Univ., Pittsburgh, PA
fYear
2008
fDate
23-28 June 2008
Firstpage
1
Lastpage
8
Abstract
We describe a preliminary investigation of utilising large amounts of unlabelled image data to help in the estimation of rough scene layout. We take the single-view geometry estimation system of Hoiem et al (2207) as the baseline and see if it is possible to improve its performance by considering a set of similar scenes gathered from the Web. The two complimentary approaches being considered are 1) improving surface classification by using average geometry estimated from the matches, and 2) improving surface segmentation by injecting segments generated from the average of the matched images. The system is evaluated using the labelled 300-image dataset of Hoiem et al. and shows promising results.
Keywords
image classification; image matching; image segmentation; rough scene layout estimation; surface classification; surface layout estimation; surface segmentation; Computational geometry; Humans; Image segmentation; Internet; Layout; Robots; Rough surfaces; Supervised learning; Surface roughness; Surface texture;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition Workshops, 2008. CVPRW '08. IEEE Computer Society Conference on
Conference_Location
Anchorage, AK
ISSN
2160-7508
Print_ISBN
978-1-4244-2339-2
Electronic_ISBN
2160-7508
Type
conf
DOI
10.1109/CVPRW.2008.4562951
Filename
4562951
Link To Document