  Contrary to the ongoing trend in automotive applications towards usage of
more diverse and more sensors, this work tries to solve the complex scene flow
problem under a monocular camera setup, i.e. using a single sensor. Towards
this end, we exploit the latest achievements in single image depth estimation,
optical flow, and sparse-to-dense interpolation and propose a monocular
combination approach (MonoComb) to compute dense scene flow. MonoComb uses
optical flow to relate reconstructed 3D positions over time and interpolates
occluded areas. This way, existing monocular methods are outperformed in
dynamic foreground regions which leads to the second best result among the
competitors on the challenging KITTI 2015 scene flow benchmark.
