Paper Info
Title
Facial landmark detection system using interest-region model and edge energy function
Abstract
In this paper, we proposed a new facial landmark-detection system using as edge energy function. The facial landmark-detection system is divided into a learning stage and a detection stage. The learning stage creates an interest-region model, to set up a search region of each landmark, as preinformation necessary for a detection stage and creates a detector for each landmark to detect a landmark in a search region. The detection stage sets up a search region of each landmark in an input image with an interest-region model created in the learning stage. Because a landmark to detect from a system has the characteristics of an edge as both edge of an eye, both edge of a mouth and both edges of eyebrows, we have detected a landmark by applying an edge energy function to the Bayesian discrimination method. We have implemented aforementioned technique by abstracting 800 impassive images from the FERET database and have measured data in which the normalized average error distance is less than 0.1 occupying 98% of the total data.
Year
DOI
Venue
2009
10.1109/ICSMC.2009.5346730
SMC
Keywords
Field
DocType
feret database,facial landmark detection system,aforementioned technique,edge energy function,new facial landmark-detection system,search region,bayesian discrimination method,total data,facial landmark-detection system,interest-region model,detection stage,face recognition,shape,data mining,edge detection,face,learning artificial intelligence,feature extraction,bayesian methods
Normalization (statistics),Edge detection,Computer science,Artificial intelligence,Detector,Facial recognition system,Computer vision,Pattern recognition,Feature extraction,FERET database,Landmark,Machine learning,Bayesian probability
Conference
ISSN
Citations 
PageRank 
1062-922X
3
0.43
References 
Authors
8
4
Name
Order
Citations
PageRank
Mi-Young Nam131.11
Zhan Yu230.43
Gi Han Kim330.43
Phill Kyu Rhee46024.82