A Dipolar Competitive Neural Network for Video Segmentation

Competitive learning
Image processing
Neural networks
Authors
Rafael Marcos Luque Baena , Domingo López-Rodríguez , Enrique Domínguez Merino , Esteban J. Palomo
Published
1 January 2008
Publication details
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), (5290 LNAI), pp. 103-112
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Abstract

This paper present a video segmentation method which separate pixels corresponding to foreground from those corresponding to background. The proposed background model consists of a competitive neural network based on dipoles, which is used to classify the pixels as background or foreground. Using this kind of neural networks permits an easy hardware implementation to achieve a real time processing with good results. The dipolar representation is designed to deal with the problem of estimating the directionality of data. Experimental results are provided by using the standard PETS dataset and compared with the mixture of Gaussians and background subtraction methods. © 2008 Springer-Verlag.

Citation

How to cite

R. M. Luque, D. López-Rodríguez, E. Domínguez, et al. “A Dipolar Competitive Neural Network for Video Segmentation”. In: Advances in Artificial Intelligence - IBERAMIA 2008, 11th Ibero-American Conference on AI, Lisbon, Portugal, October 14-17, 2008. Proceedings. Ed. by H. Geffner, R. Prada, I. M. Alexandre and N. David. Vol. 5290 LNAI. Lecture Notes in Computer Science. cited By 5; Conference of 11th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2008 ; Conference Date: 14 October 2008 Through 17 October 2008; Conference Code:77561. Lisbon: Springer, 2008, pp. 103-112. DOI: 10.1007/978-3-540-88309-8_11. URL: https://doi.org/10.1007/978-3-540-88309-8_11.

BibTeX 
<pre><code>
@InProceedings{Luque2008, author = {Rafael Marcos Luque and Domingo López-Rodríguez and Enrique Domínguez and Esteban J. Palomo}, booktitle = {Advances in Artificial Intelligence - {IBERAMIA} 2008, 11th Ibero-American Conference on AI, Lisbon, Portugal, October 14-17, 2008. Proceedings}, title = {A Dipolar Competitive Neural Network for Video Segmentation}, year = {2008}, address = {Lisbon}, editor = {Hector Geffner and Rui Prada and Isabel Machado Alexandre and Nuno David}, note = {cited By 5; Conference of 11th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2008 ; Conference Date: 14 October 2008 Through 17 October 2008; Conference Code:77561}, pages = {103-112}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, volume = {5290 LNAI}, abstract = {This paper present a video segmentation method which separate pixels corresponding to foreground from those corresponding to background. The proposed background model consists of a competitive neural network based on dipoles, which is used to classify the pixels as background or foreground. Using this kind of neural networks permits an easy hardware implementation to achieve a real time processing with good results. The dipolar representation is designed to deal with the problem of estimating the directionality of data. Experimental results are provided by using the standard PETS dataset and compared with the mixture of Gaussians and background subtraction methods. © 2008 Springer-Verlag.}, bibsource = {dblp computer science bibliography, https://dblp.org}, biburl = {https://dblp.org/rec/conf/iberamia/LuqueLDP08.bib}, document_type = {Conference Paper}, doi = {10.1007/978-3-540-88309-8_11}, journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)}, keywords = {Background model; Background subtraction method; Competitive neural network; Data sets; Hardware implementations; Mixture of Gaussians; Realtime processing; Video segmentation, Hardware; Image segmentation; Pixels, Neural networks}, source = {Scopus}, sponsors = {Lisbon University Institute (ISCTE); Fundacao para a Ciencia e Tecnologia (FCT); Asociacion Espanola de Inteligencia Artificial (AEPIA); Associacao Portuguesa para a Inteligencia Artificial (APPIA)}, url = {https://doi.org/10.1007/978-3-540-88309-8_11}, } 
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A Dipolar Competitive Neural Network for Video Segmentation

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Papers citing this work

The following is a non-exhaustive list of papers that cite this work:

  1. Thierry Bouwmans (2014). Traditional and recent approaches in background modeling for foreground detection: An overview. Computer Science Review DOI
  2. Bouwmans, Thierry (2014). Traditional Approaches in Background Modeling for Static Cameras. DOI
  3. Naveen Kumar, Shikha Chourasia, Amit Sethi (2012). An Efficient Neural Network Based Background Subtraction Method. Advances in intelligent systems and computing DOI
  4. Naveen Kumar, Ashwini Kumar Singh, Sufian Ashraf Mazhari (2012). Video Segmentation Using Neural Network and Distributed Genetic Algorithm. Advances in intelligent and soft computing DOI
  5. Ken Ryan, A. Amer, L. Gagnon (2009). Spatiotemporal Region Enhancement and Merging for Unsupervized Object Segmentation. EURASIP Journal on Image and Video Processing DOI