%Aigaion2 BibTeX export from HES SO Valais Publications
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@ARTICLE{,
     author = {Charara, Nour and Maria, Sokhn and Jarkass, Iman and Abou Khaled, Omar and Mugellini, Elena},
   keywords = {depth information, neuro-fuzzy classification, Pattern Recognition, Scene segmentation, texture},
      month = apr,
      title = {Dynamic Extended Rectangle Based Method for 3D Visual Scene Segmentation},
    journal = {International Review on Computers and Software (IRECOS)},
     volume = {8},
     number = {4},
       year = {2013},
  publisher = {Praise Worthy Prize S.r.l.},
       issn = {1828-6003},
   abstract = {a novel approach for semantic scene segmentation with computer vision is represented in this paper. The principle goal is to capture the scene distribution of the different zones of any multipurpose hall, taking into account both monocular visual cues (texture feature) and depth information. A feature extraction strategy based on a dynamic extension of the rectangular patches is proposed in order to provide a more accurate segmentaiton and to avoid redundancy penalties. The depth constraints control the initial classification decision that is obtained by a neuro-fuzzy classifier. An experimental study is applied on our dataset to demonstrate this approach on his different optimization stages.}
}