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An Integrated Framework for Robust and Fast Automatic Video Segmentation

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posted on 2023-06-08, 05:40 authored by Xiaodong Cai, Falah AliFalah Ali, E Stipidis
In this paper, we extend previous work on video segmentation [1, 2] and propose a novel integrated module-based framework for real-time applications which require automatic, precise, and fast-based features. The framework consists of five main modules: sprite generator, key frame identifier, change detector, video object plane (VOP) extractor and post-processor. A universal approach for sprite-object-based adaptive background update and a two-level change detector present the core technique of the framework. The sprite object background provides an easy way to perform segmentation automatically and the possibility of extracting video objects whenever they appear without considering the change of the background. The analysis of statistical parameter for normalized and high order statistics feature offers accurate segmentation results. The used key frames selection technique offers efficient computation. In addition, the framework targets flexible applications with different motion features by using optional modules.

History

Publication status

  • Published

Publisher

Communications Engineering Doctorate Centre, University College London

Pages

4.0

Presentation Type

  • paper

Event name

London Communications Symposium

Event location

University College London, London

Event type

conference

ISBN

9780953886326

Department affiliated with

  • Engineering and Design Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2012-02-06

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