Abstract
We propose a scheme for indoor place identification based on the recognition of global scene views. Scene views are encoded using a holistic representation that provides low-resolution spatial and spectral information. The holistic nature of the representation dispenses with the need to rely on specific objects or local landmarks and also renders it robust against variations in object configurations. We demonstrate the scheme on the problem of recognizing scenes in video sequences captured while walking through an office environment. We develop a method for distinguishing between 'diagnostic' and 'generic' views and also evaluate changes in system performances as a function of the amount of training data available and the complexity of the representation.
Keywords
Computer scienceDiscriminative modelExploitArtificial intelligenceClassifier (UML)Computer visionTask (project management)
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Publication Info
- Year
- 2009
- Type
- article
- Pages
- 413-420
- Citations
- 1464
- Access
- Closed
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Cite This
Ariadna Quattoni,
Antonio Torralba
(2009).
Recognizing indoor scenes.
2009 IEEE Conference on Computer Vision and Pattern Recognition
, 413-420.
https://doi.org/10.1109/cvpr.2009.5206537
Identifiers
- DOI
- 10.1109/cvpr.2009.5206537