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\begin{abstract}
  In the robotic field, navigation and path planning applications benefit from
  a wide range of visual systems (e.g. perspective cameras, depth cameras,
  catadioptric cameras, etc.). In outdoor conditions, these systems capture
  information in which sky regions cover a major segment of the images
  acquired. However, sky regions are discarded and are not considered as visual
  cue in vision applications.  In this paper, we propose to estimate attitude
  of \gls{uav} from sky information using a polarimetric camera. Theoretically,
  we provide a framework estimating the attitude from the skylight polarized
  patterns.
  % We showcase this formulation on simulated data sets which proved
  % the benefit of using polarimetric sensors along with other visual sensors in
  % robotic applications.
  We showcase this formulation on both simulated and real-word data
  sets which proved the benefit of using polarimetric sensors along with other
  visual sensors in robotic applications.

  % Even though sky regions often covers a major segment of acquired images in
  % robotic fields. These regions usually are not used as visual cue in vision
  % applications.  In this paper we introduce how to include these regions as a
  % main source of information for attitude estimation of \gls{uav}.  Hence we
  % propose to use a polarimetric camera to measure the skylight polarized
  % patterns and a framework connecting our measurements to attitude estimation.
  % Using the framework, we report our primary results on synthetically generated
  % datasets.  The obtained results prove the capacity of polarimetric sensors
  % for attitude estimation and promote such devices to be integrated along other
  % sensors in the robotic fields.

\end{abstract}


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\include*{content/conclusion/conclusion}



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