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Indoor-outdoor image classification
Abstract
We show how high-level scene properties can be inferred from classification of low-level image features, specifically for the indoor-outdoor scene retrieval problem. We systematically studied the features of: histograms in the Ohta color space; multiresolution, simultaneous autoregressive model parameters; and coefficients of a shift-invariant DCT. We demonstrate that performance is improved by computing features on subblocks, classifying these subblocks, and then combining these results in a way reminiscent of stacking. State of the art single-feature methods are shown to result in about 75-86% performance, while the new method results in 90.3% correct classification, when evaluated on a diverse database of over 1300 consumer images provided by Kodak.
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Cited by
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
Lazebnik, S., Schmid, C., & Ponce, J. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.68 · Cited by 7,916
Multimodal Video Indexing: A Review of the State-of-the-art
Snoek, C. G. M., & Worring, M. (2005) · Multimedia Tools and Applications · doi:10.1023/b:mtap.0000046380.27575.a5 · Cited by 486
The 2017 IEEE International Conference on Fuzzy Systems
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How realistic is photorealistic?
Lyu, S., & Farid, H. (2005) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2004.839896 · Cited by 280
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Bai, S. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.10.038 · Cited by 81
Metadata
- Authors
- Szummer, M., & Picard, R. W.
- Venue
- Proceedings 1998 IEEE International Workshop on Content-Based Access of Image and Video Database
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-27
- Pages
- 42-51
- OpenAlex
- W2104825706
- Cited by
- 639
- References
- 0
- FWCI
- 29.96
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Szummer, M., & Picard, R. W. (2002). Indoor-outdoor image classification. Proceedings 1998 IEEE International Workshop on Content-Based Access of Image and Video Database. https://doi.org/10.1109/caivd.1998.646032
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