Open AccessBackground-Foreground Segmentation Based on Dominant Motion Estimation and Static Segmentation
Author(s) -
Yu Huang,
Dietrich Paulus,
Heinrich Niemann
Publication year - 2000
Publication title -
cit. journal of computing and information technology/journal of computing and information technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.169
H-Index - 27
eISSN - 1846-3908
pISSN - 1330-1136
DOI - 10.2498/cit.2000.04.10
Subject(s) - segmentation , computer science , artificial intelligence , computer vision , motion (physics) , motion estimation , scale space segmentation , image segmentation , luminance , quarter pixel motion , measure (data warehouse) , segmentation based object categorization , data mining
This paper addresses the problem of image segmentation using motion and luminance information. We use the dominant motion model to calculate both the background and foreground motion in a robust estimation framework and then combine it with the result of static segmentation using the watershed algorithm to segment the foreground from the background. In this paper, the previous pixelbased (or over a small neighborhood) motion measure is replaced by the patch-based motion measure in motion segmentation. Experimental results are given to show the efficiency of our method