A comparison of modified evolutionary computation algorithms with applications to three-dimensional endoscopic camera motion tracking

Luo, X; Wan, Y; He, X

A comparison of modified evolutionary computation algorithms with applications to three-dimensional endoscopic camera motion tracking

Luo, X Wan, Y He, X

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Publication Type:: Conference Proceeding
Citation:: Proceedings - International Conference on Image Processing, ICIP, 2018, 2017-September pp. 3840 - 3843
Issue Date:: 2018-02-20

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Field	Value	Language
dc.contributor.author	Luo, X	en_US
dc.contributor.author	Wan, Y	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.date.issued	2018-02-20	en_US
dc.identifier.citation	Proceedings - International Conference on Image Processing, ICIP, 2018, 2017-September pp. 3840 - 3843	en_US
dc.identifier.isbn	9781509021758	en_US
dc.identifier.issn	1522-4880	en_US
dc.identifier.uri	http://hdl.handle.net/10453/119926
dc.description.abstract	© 2017 IEEE. Endoscope 3D motion tracking plays an irreplaceable role for computer-assisted endoscopy systems development. Without such tracking, it is impossible to synchronize pre- and intraoperative images in a reference coordinate frame. Currently available methods are comprised of video-based and electromagnetic tracking. These methods limit to either video image artifacts or inaccurate sensor measurements and dynamic errors. This paper proposes two modified evolutionary computation algorithms: (a) adaptive particle swarm optimization (APSO) and (b) observation-boosted differential evolution (OBDE), to augment current endoscopic camera motion tracking. The experimental results demonstrate that our modified algorithms, which combine endoscopic video images with sensor measurements to estimate endoscope movements, can improve tracking accuracy from 4.8 mm to 2.9 mm. OBDE outperforms APSO for endoscope tracking.	en_US
dc.relation.ispartof	Proceedings - International Conference on Image Processing, ICIP	en_US
dc.relation.isbasedon	10.1109/ICIP.2017.8297001	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	A comparison of modified evolutionary computation algorithms with applications to three-dimensional endoscopic camera motion tracking	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2017-September	en_US
utslib.for	080108 Neural, Evolutionary and Fuzzy Computation	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US
pubs.volume	2017-September	en_US

Abstract:

© 2017 IEEE. Endoscope 3D motion tracking plays an irreplaceable role for computer-assisted endoscopy systems development. Without such tracking, it is impossible to synchronize pre- and intraoperative images in a reference coordinate frame. Currently available methods are comprised of video-based and electromagnetic tracking. These methods limit to either video image artifacts or inaccurate sensor measurements and dynamic errors. This paper proposes two modified evolutionary computation algorithms: (a) adaptive particle swarm optimization (APSO) and (b) observation-boosted differential evolution (OBDE), to augment current endoscopic camera motion tracking. The experimental results demonstrate that our modified algorithms, which combine endoscopic video images with sensor measurements to estimate endoscope movements, can improve tracking accuracy from 4.8 mm to 2.9 mm. OBDE outperforms APSO for endoscope tracking.

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http://hdl.handle.net/10453/119926