Discovering Local Binary Pattern Equation for Foreground Object Removal
  in Videos
Caroline Pacheco do Espirito Silva Andrews Cordolino Sobral Antoine Vacavant Thierry Bouwmans Felippe De Souza
Designing a novel Local Binary Pattern (LBP) process usually relies heavily
on human experts' knowledge and experience in the area. Even experts are often
left with tedious episodes of trial and error until they identify an optimal
LBP for a particular dataset. To address this problem, we present a novel
symbolic regression able to automatically discover LBP formulas to remove the
moving parts of a scene by segmenting it into a background and a foreground.
Experimental results conducted on real videos of outdoor urban scenes under
various conditions show that the LBPs discovered by the proposed approach
significantly outperform the previous state-of-the-art LBP descriptors both
qualitatively and quantitatively. Our source code and data will be available
online.