|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
USING MARKOV RANDOM FIELD TO INTEGRATE STEREO MODULES
Kok-Guan Lim and Richard W. Prager
We present a new method using a Markov Random Field (MRF) to integrate edge and intensity based stereo algorithms. First, we derive the intensity based stereo algorithm under the MRF framework. The integration is then performed by coupling the disparity estimates from an independent edge based stereo module to the energy functional of the MRF, associated with the intensity based stereo algorithm. The maximum a posteriori estimate of the resulting MRF is obtained using the mean field annealing algorithm. Results from real and artificial images show a consistent improvement in the accuracy under this scheme of integration.
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