Paper Info
Title
Probabilistic Corner Detection for Facial Feature Extraction
Abstract
After more than 35 years of resarch, face processing is considered nowadays as one of the most important application of image analysis. It can be considered as a collection of problems (i.e., face detection, normalization, recognition and so on) each of which can be treated separately. Some face detection and face recognition techniques have reached a certain level of maturity, however facial feature extraction still represents the bottleneck of the entire process. In this paper we present a novel facial feature extraction approach that could be used for normalizing Viola-Jones detected faces and let them be recognized by an appearance-based face recognition method. For each observed feature a prior distribution is computed and used as boost map to filter the Harris corner detector response producing more feature candidates on interest region while discarding external values. Tests have been performed on both AR and BioID database using approximately 1750 faces and experimental results are very encouraging.
Year
DOI
Venue
2009
10.1007/978-3-642-04146-4_50
ICIAP
Keywords
Field
DocType
novel facial feature extraction,face detection,probabilistic corner detection,bioid database,observed feature,facial feature extraction,harris corner detector response,face recognition technique,face processing,feature candidate,appearance-based face recognition method,image analysis,feature extraction,face recognition,prior distribution,corner detection
Facial recognition system,Computer vision,Face hallucination,Feature detection (computer vision),Pattern recognition,Three-dimensional face recognition,Object-class detection,Computer science,Feature (computer vision),Feature extraction,Artificial intelligence,Face detection
Conference
Volume
ISSN
Citations 
5716
0302-9743
2
PageRank 
References 
Authors
0.37
13
3
Name
Order
Citations
PageRank
Edoardo Ardizzone123940.79
Marco La Cascia265571.39
Marco Morana311114.78