.png){kind=icon}
.png){kind=icon}
Return
Automatic moving object and background separation
.png){kind=icon}
PRE
AI
DOI：10.1016/S0165-1684(98)00007-3.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, we propose a segmentation method of reduced computational complexity aimed at separating the moving objects from the background in a generic video sequence. This task may be accomplished at the coder site to support the functionalities foreseen by new multimedia scenarios, and in particular the content-based functionalities focused by the MPEG-4 activity, allowing the user to access and decode single objects of a video sequence. The proposed algorithm discriminates between background and foreground by means of a higher-order statistics (HOS) significance test performed on a group of inter-frame differences, followed by a motion detection phase, producing a binary segmentation map. The HOS threshold is adaptively changed, based on the estimated background activity and on the potential presence of slowly moving objects. The map is refined by a final regularization stage implemented by means of a cascade of morphological filters. The algorithm performance were tested through the wide experimental activity carried out during the ISO MPEG-4 N2 Core Experiment on Automatic Segmentation Techniques, in which the authors are currently involved. Typical results obtained on MPEG4 sequences are here shown, in order to illustrate the segmentation algorithm performance. (C) 1998 Elsevier Science B.V. All rights reserved.
Keywords:
video sequence segmentation
HOS
motion detection
MPEG-4
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.6
Papers:
9.9K
Citations:
1.7W
Organization
No organization information available