Pixel Features for Self-organizing Map Based Detection of Foreground Objects in Dynamic Environments

• Molina-Cabello, Miguel A. ^[1] ; Ezequiel López-Rubio ^[1] ; Luque-Baena, Rafael Marcos ^[2] ; Enrique Domínguez ^[1] ; Palomo, Esteban J. ^{[1] [3]}
  1. [1] Universidad de Málaga

     Universidad de Málaga

     Málaga, España

     
  2. [2] Universidad de Extremadura

     Universidad de Extremadura

     Badajoz, España

     
  3. [3] Universidad Yachay Tech

     Universidad Yachay Tech

     Urcuqui, Ecuador

     

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• Localización: International Joint Conference SOCO’16-CISIS’16-ICEUTE’16: San Sebastián, Spain, October 19th-21st, 2016 Proceedings / coord. por Manuel Graña Romay , José Manuel López Guede , Oier Etxaniz, Álvaro Herrero Cosío , Héctor Quintián Pardo , Emilio Santiago Corchado Rodríguez , 2017, ISBN 978-3-319-47364-2, págs. 247-255
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Among current foreground detection algorithms for video sequences, methods based on self-organizing maps are obtaining a greater relevance. In this work we propose a probabilistic self-organising map based model, which uses a uniform distribution to represent the foreground. A suitable set of characteristic pixel features is chosen to train the probabilistic model. Our approach has been compared to some competing methods on a test set of benchmark videos, with favorable results.