@inproceedings{42c2dc4067284a37b0f896086f2052a9,
title = "A gaussian-median filter for moving objects segmentation applied for static scenarios",
abstract = "Background subtraction or also called foreground detection is an approach normally used for moving object segmentation in video sequences captured from a fixed camera. Most of the methods under this approach are not able to segment or require the strict absence of objects during their training or learning period in the first frames. In this document, a method capable of segmenting moving objects from the beginning of a video sequence and at the same time constructing a reference background image is proposed. The segmentation results show that the foreground and background regions of the scene are not affected during this stage compared to other methods.",
keywords = "Background, Foreground, Learning period, Segmentation, Video sequence",
author = "Garc{\'i}a, {Belmar Garc{\'i}a} and Funes, {Francisco J.Gallegos} and Silva, {Alberto Jorge Rosales}",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; Intelligent Systems Conference, IntelliSys 2018 ; Conference date: 06-09-2018 Through 07-09-2018",
year = "2018",
doi = "10.1007/978-3-030-01054-6_34",
language = "Ingl{\'e}s",
isbn = "9783030010539",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "478--493",
editor = "Kohei Arai and Supriya Kapoor and Rahul Bhatia",
booktitle = "Intelligent Systems and Applications - Proceedings of the 2018 Intelligent Systems Conference IntelliSys Volume 1",
address = "Alemania",
}