Abstract
State-of-the-art
methods for disparity estimation achieve good
results for single stereo frames, but temporal
coherence in stereo videos is often neglected. In
this paper, we present a method to compute
temporally coherent disparity maps. We define an
energy over whole stereo sequences and optimize
their conditional random field (CRF) distributions
using the mean-field approximation. In addition, we
introduce novel terms for smoothness and consistency
between the left and right views. We perform CRF
optimization by fast, iterative spatio-temporal
filtering with linear complexity in the total number
of pixels. We propose two CRF optimization
techniques, using parallel and sequential updates,
and compare them in detail. While parallel updates
are not guaranteed to converge, we show that, in
practice with appropriate initialization, they
provide the same quality as sequential updates and
they also lead to faster implementations. Finally,
we demonstrate that the results of our approach rank
among the state of the art while having
significantly less flickering artifacts in stereo
sequences. |
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paper
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