Coding-oriented video segmentation inspired by MRF models
Janusz Konrad, Viet-Nam Dang · 2002
This paper presents an approach to the segmentation of video sequences that is inspired by Markov random field (MRF) models and is aimed at region-based video compression. Two goals of the segmentation algorithm are considered: to assure a rate-efficient partitioning of video sequences and to provide regions that are meaningful for human observers ("coding for content"). To address both issues we extend our earlier work; we incorporate a segmentation complexity measure to account for the rate allocated to region shape, we use a robust error criterion to reject outliers in the intensity residual and we incorporate a temporal consistency constraint to assure the continuity of segmentation in time. We demonstrate improvements in the segmentation for real videoconferencing sequences.