Region growing with automatic seeding for semantic video object segmentation

Authors:
Yue Feng;Hui Fang;Jianmin Jiang
Affiliations:
EIMC, University of Bradford, UK;EIMC, University of Bradford, UK;EIMC, University of Bradford, UK
Venue:
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Year:
2005

Citing 12
Cited 1

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Video segmentation using fast marching and region growing algorithms

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The load unbalancing problem for region growing image segmentation algorithms

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Adaptive image region-growing

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Fast and automatic video object segmentation and tracking for content-based applications

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Abstract

As content-based multimedia applications become increasingly important, demand for technologies on semantic video object segmentation is growing, where the segmented objects are expected to be in line with human visual perception. Existing research is limited to semi-automatic approach, in which human intervene is often required. These include manual selection of seeds for region growing or manual classification of background edges etc. In this paper, we propose an automatic region growing algorithm for video object segmentation, which features in automatic selection of seeds and thus the entire segmentation does not require any action from human users. Experimental results show that the proposed algorithm performs well in terms of the effectiveness in video object segmentation.