ICIP 2006, Atlanta, GA

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Paper Detail

Session:Motion Estimation
Time:Tuesday, October 10, 12:00 - 12:20
Presentation: Lecture
Topic: Motion Detection and Estimation: Optical flow
Authors: Pierre-Marc Jodoin; Université de Montréal 
 Max Mignotte; Université de Montréal 
Abstract: This paper presents a differential optical flow method which accounts for two typical motion-estimation problems : (1) flow regularization within regions of uniform motion while (2) preserving sharp edges near motion discontinuities i.e., where motion is multimodal by nature. The method proposed is a modified version of the well known Lucas Kanade (LK) algorithm. Based on documented assumptions, our method computes motion with a classical least-square fit on a local neighborhood shifted away from where motion is likely to be multimodal. This edge-avoidance procedure is based on the non-parametric mean-shift algorithm which shifts the LK integration window away from local sharp edges. Our method also locally regularizes motion by performing a fusion of local motion estimates. Our method is compared with other edge-preserving methods on image sequences representing different challenges.