Optical flow robust estimation in a hybrid multi-resolution MRF framework

We propose in this paper a robust multi-resolution technique to estimate dense velocity field from image sequences. It couples a Gaussian pyramidal down-sampling decomposition together with a multi-grid approach. At each pyramid level, bilinear interpolation and efficient warping techniques are performed to generate a residual images. The displacement field is computed in a Markov Random Field (MRF) framework. We compare two different methods to minimize the Gibbs energy: a modified Iterative Conditional Mode (ICM) and a Graph-Cut algorithm extended to multi-grid scheme. We validate and demonstrate the robustness of our approach on synthetic and real images for fluid experiment applications.

• Type: Conference
• Year: 2008
• Where: ICASSP
• Authors: Cyril Cassisa, Véronique Prinet, Liang Shao, Serge Simoens, Cheng-Lin Liu
• Keywords: ICASSP 2008, Iterative Conditional Mode, Pyramidal Down-sampling Decomposition, Robust Multi-resolution Technique, Signal Processing