Share Email Print
cover

Proceedings Paper

Predefined object tracking method for video segmentation
Author(s): Daehee Kim; Minho Kim; Jae Gark Choi; Yo-Sung Ho
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

In order to support the philosophy of the MPEG-4 video coding standard, we have to represent each frame of video sequences in terms of video object planes (VOPs). Several automatic methods for segmenting of moving objects have been developed. Such algorithms separate the foreground from the background with a change detection mask, which is obtained by the difference image between two successive frames. Thus, these techniques cannot represent each individual video object in a single frame separately, i.e., object correspondence problem. In addition, those algorithms are somewhat premature to obtain desirable segmentation results from all kinds of image sequences because the mathematical model or the similarity measure for the extraction of the video object has not been defined adequately. However, if the user can define video objects in the first frame or newly appeared video objects by a partially or completely user-assisted method like the snake's algorithm, we may obtain good segmentation results over the following successive frames. This semi-automatic segmentation may be more practical in generating VOPs of moving objects. In this paper, we propose a new user-assisted video segmentation algorithm. This algorithm consists of two steps: intra-frame segmentation and inter-frame segmentation. The intra-frame segmentation is applied to the first frame of the image sequence or the frames that have newly appeared video objects. The user can manually define the newly appeared video objects in the image sequence. The inter-frame segmentation is applied to the following consecutive frames. In the inter-frame segmentation, user-defined video objects are segmented automatically by object tracking.

Paper Details

Date Published: 19 August 1998
PDF: 9 pages
Proc. SPIE 3561, Electronic Imaging and Multimedia Systems II, (19 August 1998); doi: 10.1117/12.319737
Show Author Affiliations
Daehee Kim, Kwangju Institute of Science and Technology (South Korea)
Minho Kim, Kwangju Institute of Science and Technology (South Korea)
Jae Gark Choi, Kyungil Univ. (South Korea)
Yo-Sung Ho, Kwangju Institute of Science and Technology (South Korea)


Published in SPIE Proceedings Vol. 3561:
Electronic Imaging and Multimedia Systems II
LiWei Zhou; Chung-Sheng Li, Editor(s)

© SPIE. Terms of Use
Back to Top