caa a22 4500 605468877 CHVBK 20210128100319.0 cr unu---uuuuu 210128e20150901xx s 000 0 eng 10.1007/s00500-014-1575-3 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1575-3 A self-organizing map to improve vehicle detection in flow monitoring systems [Elektronische Daten] [R. Luque-Baena, Ezequiel López-Rubio, E. Domínguez, E. Palomo, J. Jerez] The obtaining of perfect foreground segmentation masks still remains as a challenging task in video surveillance systems, since errors in that initial stage could lead to misleadings in subsequent tasks as object tracking and behavior analysis. This work presents a novel methodology based on self-organizing neural networks and Gaussian distributions to detect unusual objects in the scene, and to improve the foreground mask handling occlusions between objects. After testing the proposed approach on several traffic sequences obtained from public repositories, the results demonstrate that this methodology is promising and suitable to correct segmentation errors on crowded scenes with rigid objects. Springer-Verlag Berlin Heidelberg, 2015 Self-organizing neural networks nationallicence Postprocessing techniques nationallicence Traffic monitoring nationallicence Surveillance systems nationallicence Object detection nationallicence Luque-Baena R. Department of Computer Systems and Telematics Engineering, University of Extremadura, University Centre of Mérida, 06800, Mérida, Spain aut López-Rubio Ezequiel Department of Computer Languages and Computer Science, University of Málaga, Bulevar Louis Pasteur, 35, 29071, Málaga, Spain aut Domínguez E. Department of Computer Languages and Computer Science, University of Málaga, Bulevar Louis Pasteur, 35, 29071, Málaga, Spain aut Palomo E. Department of Computer Languages and Computer Science, University of Málaga, Bulevar Louis Pasteur, 35, 29071, Málaga, Spain aut Jerez J. Department of Computer Languages and Computer Science, University of Málaga, Bulevar Louis Pasteur, 35, 29071, Málaga, Spain aut Soft Computing Springer Berlin Heidelberg 19/9(2015-09-01), 2499-2509 1432-7643 19:9<2499 2015 19 500 https://doi.org/10.1007/s00500-014-1575-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1575-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Luque-Baena R. Department of Computer Systems and Telematics Engineering, University of Extremadura, University Centre of Mérida, 06800, Mérida, Spain aut NATIONALLICENCE 700 1- López-Rubio Ezequiel Department of Computer Languages and Computer Science, University of Málaga, Bulevar Louis Pasteur, 35, 29071, Málaga, Spain aut NATIONALLICENCE 700 1- Domínguez E. Department of Computer Languages and Computer Science, University of Málaga, Bulevar Louis Pasteur, 35, 29071, Málaga, Spain aut NATIONALLICENCE 700 1- Palomo E. Department of Computer Languages and Computer Science, University of Málaga, Bulevar Louis Pasteur, 35, 29071, Málaga, Spain aut NATIONALLICENCE 700 1- Jerez J. Department of Computer Languages and Computer Science, University of Málaga, Bulevar Louis Pasteur, 35, 29071, Málaga, Spain aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/9(2015-09-01), 2499-2509 1432-7643 19:9<2499 2015 19 500