Image Analysis and Processing, International Conference on (2001)
Sept. 26, 2001 to Sept. 28, 2001
A. Robles-Kelly , University of York
E. R. Hancock , University of York
ABSTRACT: This paper presents an iterative maximum likelihood framework for motion segmentation. Our representation of the segmentation problem is based on a similarity matrix for the motion vectors for pairs of pixel blocks. By applying eigen decomposition to the similarity matrix, we develop a maximum likelihood method for grouping the pixel blocks into objects which share a common motion vector. We experiment with the resulting clustering method on a number of real world motion sequences. Here ground truth data indicates that the method can result in motion classification errors as low as 3%.
E. R. Hancock and A. Robles-Kelly, "Maximum Likelihood Motion Segmentation Using Eigendecomposition," Image Analysis and Processing, International Conference on(ICIAP), Palermo, Italy, 2001, pp. 0063.