Abstract:
Today's stereo vision algorithms and computing technology
allow real-time 3D data analysis, for example for driver assistance
systems. A recently developed Semi-Global Matching (SGM) approach
by H. Hirschm uller became a popular choice due to performance and
robustness. This paper evaluates di erent parameter settings for SGM,
and its main contribution consists in suggesting to include a second order
prior into the smoothness term of the energy function. It also proposes
and tests a new cost function for SGM. Furthermore, some preprocessing
(edge images) proved to be of great value for improving SGM stereo
results on real-world sequences, as previously already shown by S. Guan
and R. Klette for belief propagation. There is also a performance gain for
engineered stereo data (e.g.) as currently used on the Middlebury stereo
website. However, the fact that results are not as impressive as on the
.enpeda.. sequences indicates that optimizing for engineered data does
not neccessarily improve real world stereo data analysis.
Description:
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