JOURNAL ARTICLE

<title>Predefined object tracking method for video segmentation</title>

Daehee KimMinho KimJae Gark ChoiYo‐Sung Ho

Year: 1998 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3561 Pages: 43-51   Publisher: SPIE

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.

Keywords:
Computer science Computer vision Artificial intelligence Segmentation Video tracking Frame (networking) Segmentation-based object categorization Image segmentation Scale-space segmentation Block-matching algorithm Object (grammar)

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Topics

Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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