TY  - JOUR
AU  - Katerine Diaz
AU  - Jesus Martinez del Rincon
AU  - Aura Hernandez-Sabate
AU  - Debora Gil
PY  - 2018//
TI  - Continuous head pose estimation using manifold subspace embedding and multivariate regression
T2  - ACCESS
JO  - IEEE Access
SP  - 18325
EP  - 18334
VL  - 6
KW  - Head Pose estimation
KW  - HOG features
KW  - Generalized Discriminative Common Vectors
KW  - B-splines
KW  - Multiple linear regression
N2  - In this paper, a continuous head pose estimation system is proposed to estimate yaw and pitch head angles from raw facial images. Our approach is based on manifold learningbased methods, due to their promising generalization properties shown for face modelling from images. The method combines histograms of oriented gradients, generalized discriminative common vectors and continuous local regression to achieve successful performance. Our proposal was tested on multiple standard face datasets, as well as in a realistic scenario. Results show a considerable performance improvement and a higher consistence of our model in comparison with other state-of-art methods, with angular errors varying between 9 and 17 degrees.
SN  - 2169-3536
L1  - http://refbase.cvc.uab.es/files/DMH2018b.pdf
UR  - http://dx.doi.org/10.1109/ACCESS.2018.2817252
N1  - ADAS; 600.118
ID  - Katerine Diaz2018
ER  -