2026-05-28T18:30:13Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/78692026-02-03T12:31:44Zcom_10630_2254col_10630_37959

00925njm 22002777a 4500 dc López-Rubio, Francisco Javier author López-Rubio, Ezequiel author Luque-Baena, Rafael Marcos author Domínguez-Merino, Enrique author Palomo-Ferrer, Esteban José author 2014-07-18 The selection of the best color space is a fundamental task in detecting foreground objects on scenes. In many situations, especially on dynamic backgrounds, neither grayscale nor RGB color spaces represent the best solution to detect foreground objects. Other standard color spaces, such as YCbCr or HSV, have been proposed for background modeling in the literature; although the best results have been achieved using diverse color spaces according to the application, scene, algorithm, etc. In this work, a color space and color component weighting selection process is proposed to detect foreground objects in video sequences using self-organizing maps. Experimental results are also provided using well known benchmark videos. http://hdl.handle.net/10630/7869 Modelos matemáticos Color Space Selection for Self-Organizing Map Based Foreground Detection in Video Sequences