Title :
Joint space-time image sequence segmentation based on volume competition and level sets
Author :
Konrad, Janusz ; Ristivojevic, M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Boston Univ., MA, USA
Abstract :
We address the issue of joint space-time segmentation of image sequences. Typical approaches to such segmentation consider two image frames at a time, and perform tracking of individual segments across time. We propose to perform this segmentation jointly over multiple frames. This leads to a 3D segmentation, i.e., a search for a volume "carved out" by a moving object in the (3D) image sequence domain. We pose the problem in a Bayesian framework and use the MAP criterion. Under suitable structural and segmentation/motion models we convert MAP estimation to a functional minimization. The resulting problem can be viewed as volume competition, a 3D generalization of region competition. We parameterize the unknown surface to be estimated, but rather than solving for it using an active-surface approach, we embed it into a higher-dimensional function and use the level-set methodology. We show experimental results for the simpler case of object motion against a still background although, given suitable models, the general formulation can handle complex motion too.
Keywords :
Bayes methods; image segmentation; image sequences; maximum likelihood estimation; minimisation; motion estimation; optical tracking; parameter estimation; target tracking; Bayesian framework; MAP criterion; MAP estimation; functional minimization; image segmentation; level sets; motion estimation; moving object; parameter estimation; space-time image sequence segmentation; volume competition; Active contours; Bayesian methods; Computer vision; Image analysis; Image converters; Image segmentation; Image sequences; Motion detection; Motion estimation; Motion segmentation;
Conference_Titel :
Image Processing. 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7622-6
DOI :
10.1109/ICIP.2002.1038088