Title :
Experiments in estimation of independent 3D motion using EM
Author_Institution :
Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA
Abstract :
In this paper we address the problem of multiple 3D rigid body motion estimation from the optical flow. We use the differential epipolar constraint to measure the consistency of the local flow estimates with 3D rigid body motion and employ a probabilistic interpretation of the overall flowfield in terms of mixture models. The estimation of 3D motion parameters as well as the refinement of the initial motion segmentation is carried out using an Expectation-Maximization (EM) algorithm. The algorithm is guaranteed to improve the overall likelihood of the data. The proposed technique is a step towards estimation of 3D motion of independently moving objects in the presence of egomotion
Keywords :
computer vision; image segmentation; image sequences; motion estimation; 3D motion parameters; differential epipolar constraint; egomotion; expectation maximization algorithm; local flow estimates; motion segmentation; multiple 3D rigid body motion estimation; optical flow; probabilistic interpretation; Cameras; Clustering algorithms; Computer science; Computer vision; Fluid flow measurement; Image motion analysis; Iterative algorithms; Motion detection; Motion estimation; Motion segmentation;
Conference_Titel :
Applied Imagery Pattern Recognition Workshop, AIPR 2001 30th
Conference_Location :
Washington, DC
Print_ISBN :
0-7695-1245-3
DOI :
10.1109/AIPR.2001.991217