%0 Conference Proceedings
%T Human Head Pose Estimation on SASE database using Random Hough Regression Forests
%A Iiris Lusi
%A Sergio Escalera
%A Gholamreza Anbarjafari
%B 23rd International Conference on Pattern Recognition Workshops
%D 2016
%V 10165
%F Iiris Lusi2016
%O HuPBA;
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2910), last updated on Mon, 21 Jan 2019 14:14:39 +0100
%X 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.
%U http://dx.doi.org/10.1007/978-3-319-56687-0_12