The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Dynamic texture recognition
Abstract
Dynamic textures are sequences of images that exhibit some form of temporal stationarity, such as waves, steam, and foliage. We pose the problem of recognizing and classifying dynamic textures in the space of dynamical systems where each dynamic texture is uniquely represented. Since the space is non-linear, a distance between models must be defined We examine three different distances in the space of autoregressive models and assess their power.
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Cites
An Information-Maximization Approach to Blind Separation and Blind Deconvolution
Bell, A. J., & Sejnowski, T. J. (1995) · Neural Computation · doi:10.1162/neco.1995.7.6.1129 · Cited by 8,986
Cited by
Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
Zhao, G., & Pietikainen, M. (2007) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.1110 · Cited by 2,846
A Dynamic Texture-Based Approach to Recognition of Facial Actions and Their Temporal Models
Koelstra, S., Pantic, M., & Patras, I. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.50 · Cited by 242
Metadata
- Authors
- Saisan, P., Doretto, G., Wu, Y. N., & Soatto, S.
- Venue
- Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001
- Publisher
- IEEE Comput. Soc
- Published
- 2005-08-24
- Volume
- 2
- Pages
- II-58-II-63
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2105795585
- Cited by
- 328
- References
- 1
- FWCI
- 12.76
- Type
- conference paper
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
