Extended fitting methods of active shape model for the location of facial feature points

Du, C; Yang, J; Wu, Q; Zhang, T; Wang, H; Chen, L; Wu, Z

Extended fitting methods of active shape model for the location of facial feature points

Du, C Yang, J Wu, Q

Zhang, T Wang, H Chen, L Wu, Z

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Publisher:: Springer
Publication Type:: Journal Article
Citation:: Lecture notes in computer science, 2006, 4338 pp. 610 - 618
Issue Date:: 2006-01

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Field	Value	Language
dc.contributor.author	Du, C	en_US
dc.contributor.author	Yang, J	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.contributor.author	Zhang, T	en_US
dc.contributor.author	Wang, H	en_US
dc.contributor.author	Chen, L	en_US
dc.contributor.author	Wu, Z	en_US
dc.date.issued	2006-01	en_US
dc.identifier.citation	Lecture notes in computer science, 2006, 4338 pp. 610 - 618	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/4999
dc.description.abstract	In this study, we propose three extended fitting methods to the standard ASM(active shape model). Firstly, profiles are extended from ID to 2D; Secondly, profiles of different landmarks are constructed individually; Thirdly, length of the profiles is determined adaptively with the change of level during searching, and the displacements in the last level are constrained. Each method and the combination of three methods are tested on the SJTU(Shanghai Jiaotong University) face database. In all cases, compared to the standard ASM, each method improves the accuracy or speed in a way, and the combination of three methods improves the accuracy and speed greatly.	en_US
dc.publisher	Springer	en_US
dc.relation.ispartof	Lecture notes in computer science	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Extended fitting methods of active shape model for the location of facial feature points	en_US
dc.type	Journal Article
utslib.citation.volume	4338	en_US
utslib.for	0807 Library and Information Studies	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 - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.consider-herdc	true	en_US
pubs.volume	4338	en_US

Abstract:

In this study, we propose three extended fitting methods to the standard ASM(active shape model). Firstly, profiles are extended from ID to 2D; Secondly, profiles of different landmarks are constructed individually; Thirdly, length of the profiles is determined adaptively with the change of level during searching, and the displacements in the last level are constrained. Each method and the combination of three methods are tested on the SJTU(Shanghai Jiaotong University) face database. In all cases, compared to the standard ASM, each method improves the accuracy or speed in a way, and the combination of three methods improves the accuracy and speed greatly.

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http://hdl.handle.net/10453/4999