Recognizing indoor scenes
Author(s)
Quattoni, Ariadna; Torralba, Antonio
DownloadQuattoni-2009-Recognizing indoor scenes.pdf (1.718Mb)
PUBLISHER_POLICY
Publisher Policy
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Terms of use
Metadata
Show full item recordAbstract
Indoor scene recognition is a challenging open problem in high level vision. Most scene recognition models that work well for outdoor scenes perform poorly in the indoor domain. The main difficulty is that while some indoor scenes (e.g. corridors) can be well characterized by global spatial properties, others (e.g, bookstores) are better characterized by the objects they contain. More generally, to address the indoor scenes recognition problem we need a model that can exploit local and global discriminative information. In this paper we propose a prototype based model that can successfully combine both sources of information. To test our approach we created a dataset of 67 indoor scenes categories (the largest available) covering a wide range of domains. The results show that our approach can significantly outperform a state of the art classifier for the task.
Date issued
2009-08Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer ScienceJournal
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR 2009.
Publisher
Institute of Electrical and Electronics Engineers
Citation
Quattoni, A., and A. Torralba. “Recognizing indoor scenes.” Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on. 2009. 413-420. © Copyright 2009 IEEE
Version: Final published version
Other identifiers
INSPEC Accession Number: 10836098
ISBN
978-1-4244-3992-8
ISSN
1063-6919