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\label{sec:opticalflow}  Optical flow estimates the motion based on successive images: the shift of corresponding image keypoints in $x,y$-direction.  The approach is computationally rather complex. It is a relative localization method: without an initial reference point, it can only estimate the distance to an initial reference point but not its absolute position in space. The approach suffers from drift: since the distance travelled is based on comparing successive images, errors are accumulating over time. The approach alone does not have the the possibility to correct these errors. \citet{} McGuire introduces a lightweight optical flow algorithm that is able to run on-board of an MAV. The algorithm uses compressed representations of images in the form of edge histogram to calculate the flow.