Video object encoder using region-of-interest based neural network classifiers

T. Jan

doi:10.1109/ISSPIT.2003.1341110

Video object encoder using region-of-interest based neural network classifiers

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, a hybrid classifier is introduced which combines a linear discriminant classifier and a nonlinear non-parametric neural network based classifier such as the radial basis function neural networks. This hybrid model provides a linear parametric coding of the coarse-level information about the underlying image, and then uses the neural networks to encode the finer-level information of the same image. This model allows the selected image regions of interest be analyzed and encoded in the finer scales by a non-parametric neural network models whilst the image regions of no-interest are analyzed and encoded in coarse scales by a simple parametric model. The experiment on video image compression shows that the proposed model achieves significantly reduced computations for similar compression performance compared to other conventional methods.

Original language	English
Title of host publication	Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	263-266
Number of pages	4
ISBN (Electronic)	0780382927, 9780780382923
DOIs	https://doi.org/10.1109/ISSPIT.2003.1341110
Publication status	Published - 2003
Externally published	Yes
Event	3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003 - Darmstadt, Germany Duration: 14 Dec 2003 → 17 Dec 2003

Publication series

Name	Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003

Conference

Conference	3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003
Country/Territory	Germany
City	Darmstadt
Period	14/12/03 → 17/12/03

Keywords

Artificial neural networks
Computer networks
Humans
Image analysis
Image coding
Information processing
Linear discriminant analysis
Neural networks
Object oriented modeling
Video compression

Access to Document

10.1109/ISSPIT.2003.1341110

Cite this

Jan, T. (2003). Video object encoder using region-of-interest based neural network classifiers. In Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003 (pp. 263-266). Article 1341110 (Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSPIT.2003.1341110

Jan, T. / Video object encoder using region-of-interest based neural network classifiers. Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003. Institute of Electrical and Electronics Engineers Inc., 2003. pp. 263-266 (Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003).

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title = "Video object encoder using region-of-interest based neural network classifiers",

abstract = "In this paper, a hybrid classifier is introduced which combines a linear discriminant classifier and a nonlinear non-parametric neural network based classifier such as the radial basis function neural networks. This hybrid model provides a linear parametric coding of the coarse-level information about the underlying image, and then uses the neural networks to encode the finer-level information of the same image. This model allows the selected image regions of interest be analyzed and encoded in the finer scales by a non-parametric neural network models whilst the image regions of no-interest are analyzed and encoded in coarse scales by a simple parametric model. The experiment on video image compression shows that the proposed model achieves significantly reduced computations for similar compression performance compared to other conventional methods.",

keywords = "Artificial neural networks, Computer networks, Humans, Image analysis, Image coding, Information processing, Linear discriminant analysis, Neural networks, Object oriented modeling, Video compression",

author = "T. Jan",

note = "Publisher Copyright: {\textcopyright} 2003 IEEE.; 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003 ; Conference date: 14-12-2003 Through 17-12-2003",

year = "2003",

doi = "10.1109/ISSPIT.2003.1341110",

language = "English",

series = "Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "263--266",

booktitle = "Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003",

}

Jan, T 2003, Video object encoder using region-of-interest based neural network classifiers. in Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003., 1341110, Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003, Institute of Electrical and Electronics Engineers Inc., pp. 263-266, 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003, Darmstadt, Germany, 14/12/03. https://doi.org/10.1109/ISSPIT.2003.1341110

Video object encoder using region-of-interest based neural network classifiers. / Jan, T.
Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003. Institute of Electrical and Electronics Engineers Inc., 2003. p. 263-266 1341110 (Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In this paper, a hybrid classifier is introduced which combines a linear discriminant classifier and a nonlinear non-parametric neural network based classifier such as the radial basis function neural networks. This hybrid model provides a linear parametric coding of the coarse-level information about the underlying image, and then uses the neural networks to encode the finer-level information of the same image. This model allows the selected image regions of interest be analyzed and encoded in the finer scales by a non-parametric neural network models whilst the image regions of no-interest are analyzed and encoded in coarse scales by a simple parametric model. The experiment on video image compression shows that the proposed model achieves significantly reduced computations for similar compression performance compared to other conventional methods.

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KW - Computer networks

KW - Humans

KW - Image analysis

KW - Image coding

KW - Information processing

KW - Linear discriminant analysis

KW - Neural networks

KW - Object oriented modeling

KW - Video compression

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BT - Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003

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Jan T. Video object encoder using region-of-interest based neural network classifiers. In Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003. Institute of Electrical and Electronics Engineers Inc. 2003. p. 263-266. 1341110. (Proceedings of the 3rd IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2003). doi: 10.1109/ISSPIT.2003.1341110

Video object encoder using region-of-interest based neural network classifiers

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