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Automatic Bootstrapping and Tracking of Object Contours

John Chiverton, Xianghua Xie Orcid Logo, Majid Mirmehdi

IEEE Transactions on Image Processing, Volume: 21, Issue: 3, Pages: 1231 - 1245

Swansea University Author: Xianghua Xie Orcid Logo

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DOI (Published version): 10.1109/TIP.2011.2167343

Abstract

This work introduces a new fully automatic object tracking and segmentation framework. The framework consists of a motion based bootstrapping algorithm concurrent to a shape based active contour. The shape based active contour uses a finite shape memory that is automatically and continuously built f...

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Published in: IEEE Transactions on Image Processing
ISSN: 1057-7149
Published: USA IEEE Computer Society 2012
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URI: https://cronfa.swan.ac.uk/Record/cronfa7783
Abstract: This work introduces a new fully automatic object tracking and segmentation framework. The framework consists of a motion based bootstrapping algorithm concurrent to a shape based active contour. The shape based active contour uses a finite shape memory that is automatically and continuously built from both the bootstrap process and the active contour object tracker. A scheme is proposed to ensure the finite shape memory is continuously updated but forgets unnecessary information. Two new ways of automatically extracting shape information from image data given a region of interest are also proposed. Results demonstrate that the bootstrapping stage provides important motion and shape information to the object tracker.
College: Faculty of Science and Engineering
Issue: 3
Start Page: 1231
End Page: 1245

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