Title :
Facial feature detection using Conditional Regression Forests
Author :
Vural, Gencer ; Gokmen, Muhittin
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Istanbul Tek. Univ., İstanbul, Turkey
Abstract :
Even though there are many studies on facial feature detection from two dimensional still images, real-time facial feature detection is one of fresh fields. In this paper, a structure including Conditional Regression Forest and Local Zernike Moments is introduced to solve this problem. In this study, regression forests learn the relations between facial image patches and location of facial feature points conditional to head pose. This method is evaluated on Labeled Faces in the Wild (LFW) [2] database and promising results are obtained.
Keywords :
face recognition; feature extraction; polynomials; pose estimation; regression analysis; conditional regression forest; facial feature detection; facial feature point location; facial image patch; head pose; local Zernike moment; Computational modeling; Databases; Face recognition; Facial features; Real-time systems; Conditional Regression Forests; Local Zernike Moments; Real-time Facial Feature Detection;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
DOI :
10.1109/SIU.2015.7130080