RT info:eu-repo/semantics/article
T1 Face pose estimation with automatic 3D model creation in challenging scenarios
A1 Jiménez Molina, Pedro
A1 Bergasa Pascual, Luis Miguel
A1 Nuevo Chiquero, Jesús
A1 Fernández Alcantarilla, Pablo
K1 3D face pose estimation
K1 Face model
K1 Yaw rotation
K1 Feature re-registering
K1 Stereo vision
K1 Electrónica
K1 Electronics
AB This paper proposes a new method to perform real-time face pose estimation for ± 90° yaw rotations and under low light conditions. The algorithm works on the basis of a completely automatic and run-time incremental 3D face modelling. The model is initially made up upon a set of 3D points derived from stereo grey-scale images. As new areas of the subject face appear to the cameras, new 3D points are automatically added to complete the model. In this way, we can estimate the pose for a wide range of rotation angles, where typically 3D frontal points are occluded. We propose a new feature re-registering technique which combines views of both cameras of the stereo rig in a smart way in order to perform a fast and robust tracking for the full range of yaw rotations. The Levenberg–Marquardt algorithm is used to recover the pose and a RANSAC framework rejects incorrectly tracked points.The model is continuously optimised in a bundle adjustment process that reduces the accumulated error on the 3D reconstruction. The intended application of this work is estimating the focus of attention of drivers in a simulator, which imposes challenging requirements. We validate our method on sequences recorded in a naturalistic truck simulator, on driving exercises designed by a team of psychologists.
PB Elsevier
SN 0262-8856
YR 2012
FD 2012-09
LK http://hdl.handle.net/10017/43367
UL http://hdl.handle.net/10017/43367
LA eng
NO Ministerio de Ciencia e Innovación
DS MINDS@UW
RD 18-abr-2024