TY  - CONF
AU  - Iiris Lusi
AU  - Sergio Escalera
AU  - Gholamreza Anbarjafari
A2  - ICPRW
PY  - 2016//
TI  - Human Head Pose Estimation on SASE database using Random Hough Regression Forests
T2  - LNCS
BT  - 23rd International Conference on Pattern Recognition Workshops
VL  - 10165
N2  - In recent years head pose estimation has become an important task in face analysis scenarios. Given the availability of high resolution 3D sensors, the design of a high resolution head pose database would be beneficial for the community. In this paper, Random Hough Forests are used to estimate 3D head pose and location on a new 3D head database, SASE, which represents the baseline performance on the new data for an upcoming international head pose estimation competition. The data in SASE is acquired with a Microsoft Kinect 2 camera, including the RGB and depth information of 50 subjects with a large sample of head poses, allowing us to test methods for real-life scenarios. We briefly review the database while showing baseline head pose estimation results based on Random Hough Forests.
UR  - http://dx.doi.org/10.1007/978-3-319-56687-0_12
N1  - HuPBA;
ID  - Iiris Lusi2016
ER  -