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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
first_indexed 2013-07-23T11:59:23Z
last_indexed 2019-06-14T19:03:55Z
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spelling 2019-06-14T15:36:56.8422464 v2 7783 2012-02-23 Automatic Bootstrapping and Tracking of Object Contours b334d40963c7a2f435f06d2c26c74e11 0000-0002-2701-8660 Xianghua Xie Xianghua Xie true false 2012-02-23 MACS 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. Journal Article IEEE Transactions on Image Processing 21 3 1231 1245 IEEE Computer Society USA 1057-7149 1 3 2012 2012-03-01 10.1109/TIP.2011.2167343 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6015548 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University 2019-06-14T15:36:56.8422464 2012-02-23T17:02:15.0000000 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science John Chiverton 1 Xianghua Xie 0000-0002-2701-8660 2 Majid Mirmehdi 3 0007783-20042015170446.pdf tip2012Chiverton.pdf 2015-04-20T17:04:46.6370000 Output 2356185 application/pdf Version of Record true 2015-04-20T00:00:00.0000000 true
title Automatic Bootstrapping and Tracking of Object Contours
spellingShingle Automatic Bootstrapping and Tracking of Object Contours
Xianghua Xie
title_short Automatic Bootstrapping and Tracking of Object Contours
title_full Automatic Bootstrapping and Tracking of Object Contours
title_fullStr Automatic Bootstrapping and Tracking of Object Contours
title_full_unstemmed Automatic Bootstrapping and Tracking of Object Contours
title_sort Automatic Bootstrapping and Tracking of Object Contours
author_id_str_mv b334d40963c7a2f435f06d2c26c74e11
author_id_fullname_str_mv b334d40963c7a2f435f06d2c26c74e11_***_Xianghua Xie
author Xianghua Xie
author2 John Chiverton
Xianghua Xie
Majid Mirmehdi
format Journal article
container_title IEEE Transactions on Image Processing
container_volume 21
container_issue 3
container_start_page 1231
publishDate 2012
institution Swansea University
issn 1057-7149
doi_str_mv 10.1109/TIP.2011.2167343
publisher IEEE Computer Society
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6015548
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description 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.
published_date 2012-03-01T03:15:15Z
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score 11.089386

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