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 :
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