Human pose estimation has been actively studied for decades. While traditional approaches rely on 2d data like images or videos, the development of Time-of-Flight cameras and other depth sensors created new opportunities to advance the field. We give an overview of recent approaches that perform human motion analysis which includes depthbased and skeleton-based activity recognition, head pose e...

We study the problem of multi-person pose estimation in natural images. A pose estimate describes the spatial position and identity (head, foot, knee, etc.) of every non-occluded body part of a person. Pose estimation is difficult due to issues such as deformation and variation in body configurations and occlusion of parts, while multi-person settings add complications such as an unknown number...

We present a new scheme to robustly detect a type of human attentive behavior, which we call frequent change in focus of attention (FCFA), from video sequences. FCFA behavior can be easily perceived by people as temporal changes of human head pose (normally the pan angle). For recognition of this behavior by computer, we propose an algorithm to estimate the head pan angle in each frame of the s...

Head pose is an important indicator of a person’s focus of attention. Also, head pose estimation can be used as the front-end analysis for multi-view face analysis. For example, face recognition and identification algorithms are usually view dependent. Pose classification can help such face recognition systems to select the best view model. Subspace analysis has been widely used for head pose e...

Main purpose of this thesis is to study a facial feature based human head pose estimation. Especially the facial feature extraction methods suitable for a real-time system are considered. Based on the literature survey, an experimental head tracking and pose estimation system is implemented. An efficient method based on skin detection, gray-scale morphology and a geometrical face model are appl...

An automatic video-conferencing system is proposed which employs acoustic source localization, video face tracking and pose estimation, and multi-channel speech enhancement. The video portion of the system tracks talkers by utilizing source motion, contour geometry, color data, and simple facial features. Decisions involving which camera to use are based on an estimate of the head’s gazing angl...

In the task of analyzing image of individuals, head pose is one of the most vital pieces of information ones can acquired from the image. Thus, several researchers have attempted to find a way to automatically extract such information with sufficient accuracy. On the other hand, due to the increasing of surveillance system which generally produce head images in low resolution, many researchers ...

In this paper, we present two systems that were used for head pose estimation during the CLEAR06 Evaluation. We participated in two tasks: (1) estimating both pan and tilt orientation on synthetic, high resolution head captures, (2) estimating horizontal head orientation only on real seminar recordings that were captured with multiple cameras from different viewing angles. In both systems, we u...

Evaluation of driving performance is of utmost importance in order to reduce road accident rate. Since driving ability includes visual-spatial and operational attention, among others, head pose estimation of the driver is a crucial indicator of driving performance. This paper proposes a new automatic method for coarse and fine head’s yaw angle estimation of the driver. We rely on a set of geome...

Subspace analysis has been widely used for head pose estimation. However, such techniques are usually sensitive to data alignment and background noise. In this paper a two-stage approach is proposed to address this issue by combining the subspace analysis together with the topography method. The first stage is based on the subspace analysis of Gabor wavelets responses. Different subspace techni...