Maâmatou et al. EURASIP Journal on Image and Video Processing (2017) 2017:5 DOI 10.1186/s13640-016-0154-1 EURASIP Journal on Image and Video Processing ERRATUM Open Access Erratum to: Sequential Monte Carlo filter based on multiple strategies for a scene specialization classifier Houda Maâmatou1,2,3*, Thierry Chateau1, Sami Gazzah2, Yann Goyat3 and Najoua Essoukri Ben Amara2 Erratum In this version of this article that was originally published [1] there were errors in the titles of Figures 11 and 12. The titles should be as follows: Figure 11: Comparison of sample-proposal strategies. Pedestrian detection: a CUHK_Square dataset and b MIT traffic dataset. Car detection: c MIT traffic dataset and d Logiroad traffic dataset. And Figure 12: Comparison of both observation strategies. Pedestrian detection: a CUHK_Square dataset and b MIT traffic dataset. Car detection: c MIT traffic dataset and d Logiroad traffic dataset. The original article has been revised. The publisher apologises for these errors. Author details 1 Institut Pascal, Blaise Pascal University, 24 Avenue des Landais, Clermont-Ferrand, France. 2SAGE ENISo, University of Sousse, BP 264 Sousse Erriadh, Sousse, Tunisia. 3Logiroad, 2 Rue Robert Schuman, Nantes, France. Received: 15 December 2016 Accepted: 15 December 2016 Reference 1. H Maâmatou, T Chateau, S Gazzah, Y Goyat, NEB Amara, Sequential Monte Carlo filter based on multiple strategies for a scene specialization classifier. EURASIP Journal on Image and Video Processing 2016, 40 (2016) * Correspondence: [email protected] 1 Institut Pascal, Blaise Pascal University, 24 Avenue des Landais, Clermont-Ferrand, France 2 SAGE ENISo, University of Sousse, BP 264 Sousse Erriadh, Sousse, Tunisia Full list of author information is available at the end of the article © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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