Thomas Müller, Clemens Rabe, Jens Rannacher, Uwe Franke, Rudolf MesterAbstractVision-based motion perception builds primarily on the concept of
optical flow. Modern optical flow approaches suffer from several
shortcomings, especially in real, non-ideal scenarios such as traffic
scenes. Non-constant illumination conditions in consecutive frames of
the input image sequence are among these shortcomings. We propose and
evaluate the application of intrinsically illumination-invariant census
transforms within a dense state-of-the-art variational optical flow
computation scheme. Our technique improves robustness against
illumination changes, caused either by altering physical illumination or
camera parameter adjustments. Since census signatures can be
implemented quite efficiently, the resulting optical flow fields can be
computed in real-time.
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