Over the last decade, a driver's distraction has gained popularity due to its increased
significance and high impact on road accidents. Various factors, such as mood disorder …

We address the problem of fine-grain head pose angle estimation from a single 2D face
image as a continuous regression problem. Currently the state of the art, and a promising …

Head pose classification from surveillance images acquired with distant, large field-of-view
cameras is difficult as faces are captured at low-resolution and have a blurred appearance …

In this paper we propose a framework for learning a regression function form a set of local
features in an image. The regression is learned from an embedded representation that …

Fine-grain head pose estimation from imagery is an essential operation for many human-
centered systems, including pose independent face recognition and human-computer …

In this paper, we present a head pose estimation method for unconstrained images using
feature-based manifold embedding. The main challenge of manifold embedding methods is …

Head yaw angle is an important indicator of a driver's distraction. Forward collision warning
systems incorporate head yaw angle estimators for detecting driver's head-off-road glances …

Head poses can be automatically estimated using manifold learning algorithms, with the
assumption that with the pose being the only variable, the face images should lie in a …

Multi-view head-pose estimation in low-resolution, dynamic scenes is difficult due to blurred
facial appearance and perspective changes as targets move around freely in the …

In this paper, we study the identity-independent head pose estimation problem, in order to
handle the appearance variations, we consider the pose data lying on multiple manifolds …