Authors:
Mohamed Selim
1
;
Ahmet Firintepe
2
;
Alain Pagani
1
and
Didier Stricker
1
Affiliations:
1
German Research Center for Artificial Intelligence (DFKI), Trippstadter Str. 122, Kaiserslautern, Germany
;
2
BMW Group, Munich, Germany
Keyword(s):
Driving, Head Pose Estimation, Deep Learning, Infrared Camera, Kinect V2, Eye Gaze.
Abstract:
In computer vision research, public datasets are crucial to objectively assess new algorithms. By the wide use of deep learning methods to solve computer vision problems, large-scale datasets are indispensable for proper network training. Various driver-centered analysis depend on accurate head pose and gaze estimation. In this paper, we present a new large-scale dataset, AutoPOSE. The dataset provides ∼ 1.1M IR images taken from the dashboard view, and ∼ 315K from Kinect v2 (RGB, IR, Depth) taken from center mirror view. AutoPOSE’s ground truth -head orientation and position-was acquired with a sub-millimeter accurate motion capturing system. Moreover, we present a head orientation estimation baseline with a state-of-the-art method on our AutoPOSE dataset. We provide the dataset as a downloadable package from a public website.