Title :
Real time facial feature points tracking with Pyramidal Lucas-Kanade algorithm
Author :
Abdat, F. ; Maaoui, C. ; Pruski, A.
Author_Institution :
Lab. d´´Autom. des Syst. Cooperatifs, Univ. de Metz., Metz
Abstract :
In this paper, we present a detection and tracking feature points algorithm in real time camera input environment. To trace and extract a face image, we use a modified face detector based on the Haar-like features. For feature points detection, we use good features to track of Shi and Thomasi. In order to track the facial feature points, pyramidal Lucas-Kanade feature tracker algorithm is used. Results on the real time indicate that the proposed algorithm can accurately extract facial features points.
Keywords :
face recognition; feature extraction; tracking; Haar-like feature point detection; face image extraction; modified face detector; pyramidal Lucas-Kanade algorithm; real time camera input environment; real time facial feature point tracking; Application software; Classification tree analysis; Computer vision; Detectors; Face detection; Face recognition; Facial features; Real time systems; Shape; Solid modeling;
Conference_Titel :
Robot and Human Interactive Communication, 2008. RO-MAN 2008. The 17th IEEE International Symposium on
Conference_Location :
Munich
Print_ISBN :
978-1-4244-2212-8
Electronic_ISBN :
978-1-4244-2213-5
DOI :
10.1109/ROMAN.2008.4600645