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Analysis of Human Face Shape Abnorma...

Wu, Jia.

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Analysis of Human Face Shape Abnormalities Using Machine Learning.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analysis of Human Face Shape Abnormalities Using Machine Learning./
Author:	Wu, Jia.
Description:	90 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-12(E), Section: B.
Contained By:	Dissertation Abstracts International75-12B(E).
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3631997
ISBN:	9781321112160

Analysis of Human Face Shape Abnormalities Using Machine Learning.
Wu, Jia.

Analysis of Human Face Shape Abnormalities Using Machine Learning. - 90 p.

Source: Dissertation Abstracts International, Volume: 75-12(E), Section: B.

Thesis (Ph.D.)--University of Washington, 2014.

This item must not be sold to any third party vendors.

Because the capture of 3D facial form for people with medical conditions has become a practical reality, much research has been done using computer-based automatic methods to study 3D facial characteristics. This study focuses on face abnormality, especially, children with cleft lip and/or palate.

ISBN: 9781321112160Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Analysis of Human Face Shape Abnormalities Using Machine Learning.
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020 $a 9781321112160
035 $a (MiAaPQ)AAI3631997
035 $a AAI3631997
040 $a MiAaPQ $c MiAaPQ
100 1 $a Wu, Jia. $3 1922800
245 1 0 $a Analysis of Human Face Shape Abnormalities Using Machine Learning.
300 $a 90 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-12(E), Section: B.
500 $a Adviser: Linda G. Shapiro.
502 $a Thesis (Ph.D.)--University of Washington, 2014.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a Because the capture of 3D facial form for people with medical conditions has become a practical reality, much research has been done using computer-based automatic methods to study 3D facial characteristics. This study focuses on face abnormality, especially, children with cleft lip and/or palate.
520 $a Cleft lip is a birth defect that results in deformity of the upper lip and nose. Its severity is widely variable and the results of treatment are influenced by the initial deformity. Objective assessment of severity would help to guide prognosis and treatment. Given that facial asymmetry increases directly with increasing cleft severity, the main focus of this thesis is the quantification of asymmetry and nasal deformity.
520 $a In our study, we developed an automated computer-based system for facial analysis that can greatly facilitate medical researchers. Our system takes raw 3D data, automatically crops the region of interest (the face), and normalizes the 3D face mesh. Then 20 landmarks are automatically located using geometric information followed by a deformable registration method. These landmarks are used for locating the mid-facial reference plane, which sets up the reference to compare the left and right side of the face. The plane is used to provide a ranking order based on the severity of cleft lip using a learning-to-rank algorithm. Last but not least, asymmetry and nasal deformity descriptors are calculated to provide quantitative scores. The main contributions of this work are: an automated methodology for cleaning raw data and pose normalization; an automated landmark location method; a machine learning technique that detect landmark-related regions; two original algorithms to find the mid-facial reference planes and their evaluation; features for ranking the severity of cleft lip; and six descriptors for asymmetry and nasal deformity, which are highly correlated to the ranking orders provided by medical expert.
590 $a School code: 0250.
650 4 $a Engineering, Electronics and Electrical. $3 626636
690 $a 0544
710 2 $a University of Washington. $b Electrical Engineering. $3 2102369
773 0 $t Dissertation Abstracts International $g 75-12B(E).
790 $a 0250
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3631997