Generic Face Alignment using Active Shape Model with Supportector Machine
Date Issued
2008
Date
2008
Author(s)
Sheng-Shau, Peng
Abstract
Active Shape Model(ASM) causes great attention in recent years, it can be used in many different application including medical imaging,ace alignment etc. One of the characteristic of ASM is combining shape and intensity, with carefully training it can locate featuresn given image . But due to some assumption and approxiamation, sometimes the search falls into local minima.n the other hand, Support Vector Machine is a tool that many researcher use in machine learning or pattern recognition area.ts advantage is the speed of training and classification although the performance is highly relative to training samples.n this paper, we propose a novel view in face alignment. With combining ASM and SVM, we obtain additional information instead ofocal intensity. These information help the search away from local minima and improve the performance of alignment.
Subjects
Active Shape Model(ASM)
face alignment
Support Vector Machine(SVM)
eigenface
face tracking
face recognition
Type
thesis
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