1997
DOI: 10.1002/(sici)1520-684x(199709)28:10<77::aid-scj9>3.3.co;2-j
|View full text |Cite
|
Sign up to set email alerts
|

Basis generation and description of facial images using principal‐component analysis

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2011
2011
2011
2011

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 0 publications
0
1
0
Order By: Relevance
“…3-D data handling, measurement, and visualization were done using 3D-Rugle version 4, and most statistical calculations with Systat version 10. The principal component axes were morphologically expressed by deforming the 273-point grid by the eigenshape method (Nagata et al, 1996;Isono et al, 1999;Kuratate et al, 1999Kuratate et al, , 2003MacLeod, 1999) using the routines Bone Restorer and Proc 3D written by one of us (S.M. ).…”
Section: Methodsmentioning
confidence: 99%
“…3-D data handling, measurement, and visualization were done using 3D-Rugle version 4, and most statistical calculations with Systat version 10. The principal component axes were morphologically expressed by deforming the 273-point grid by the eigenshape method (Nagata et al, 1996;Isono et al, 1999;Kuratate et al, 1999Kuratate et al, , 2003MacLeod, 1999) using the routines Bone Restorer and Proc 3D written by one of us (S.M. ).…”
Section: Methodsmentioning
confidence: 99%