Title :
Supervised Learning for Head Pose Estimation Using SVD and Gabor Wavelets
Author :
Lablack, A. ; Zhongfei Zhang ; Djeraba, C.
Author_Institution :
LIFL, Univ. de Lille 1, Lille
Abstract :
This paper presents the use of a template based method in order to make a head pose estimation. As an image classification problem the aim of this kind of techniques is to convert the input head image into a feature vector. The feature vectors of different persons taken at the same pose will serve to learn a head pose classifier. The aim of this work is to estimate the head pose of people looking at a target scene in order to extract the location of their gaze in the scene.
Keywords :
image classification; learning (artificial intelligence); pose estimation; singular value decomposition; wavelet transforms; Gabor wavelets; SVD; feature vector; head pose classifier; head pose estimation; image classification; supervised learning; template based method; Eyes; Facial features; Head; Image classification; Layout; Solid modeling; State estimation; Supervised learning; Support vector machines; USA Councils; Feature extraction; Head pose estimation; Supervised learning;
Conference_Titel :
Multimedia, 2008. ISM 2008. Tenth IEEE International Symposium on
Conference_Location :
Berkeley, CA
Print_ISBN :
978-0-7695-3454-1
DOI :
10.1109/ISM.2008.34
