Recognizing indoor scenes
Name
Quattoni-2009-Recognizing indoor scenes.pdf
Size
1.72 MB
Format
Adobe PDF
Checksum (MD5)
b6437bb9d11cf7aaa6f896952b7fa036
Author(s)
Quattoni, Ariadna
Torralba, Antonio
Date Issued
August 2009
Journal
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
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/CVPRW.2009.5206537
