This article presents a multimodal approach to head pose estimation of individuals in environments equipped with multiple cameras and microphones, such as SmartRooms or automatic video conferencing. Determining the individuals head orientation is the basis for many forms of more sophisticated interactions between humans and technical devices and can also be used for automatic sensor selection (...

This thesis focuses on data mining technologies to extract head pose information from low resolution video recordings. Head pose, as an approximation of gaze direction, is a key indicator of human behavior and interaction. Extracting head pose information from video recordings is a labor intensive endeavor that severely limits the feasibility of using large video corpora to perform tasks that r...

We propose to use a state-of-the-art visual odometry technique for the purpose of head pose estimation. We demonstrate that with small adaptation this algorithm allows to achieve more accurate head pose estimation from an RGBD sensor than all the methods published to date. We also propose a novel methodology to automatically assess the accuracy of a tracking algorithm without the need to manual...

Head pose can indicate the eye-gaze direction and face toward which is an important part of human motion estimation and understanding. Due to physical factors of the camera, shooting environment, as well as the appearance change of humanity, the head pose estimation becomes a challenging task. Synchronization sub manifold embedding can find the internal structure of nonlinear data for nonlinear...

Abstract Nowadays, face detection and head pose estimation have a lot of application such as recognition, aiding in gaze modeling attention. For these two tasks, it is usually to design different models. However, the model often depends on region interest (ROI) detected advance, which means that serial detector needed. Even lightest will slow down whole forward inference time cannot achieve rea...

This paper addresses the problem of estimating head pose over a wide range of angles from low-resolution images. Faces are detected using chrominance-based features. Grey-level normalized face imagettes serve as input for linear auto-associative memory. One memory is computed for each pose using a Widrow-Hoff learning rule. Head pose is classified with a winner-takes-all process. We compare res...

This paper proposes a novel method to improve the accuracy of head pose estimation. Since biologically inspired features (BIF) have been demonstrated to be both effective and efficient for many visual tasks, we argue that BIF can be applied to the problem of head pose estimation. By combining the BIF with the well-known local binary pattern (LBP) feature, we propose a novel feature descriptor n...

For many practical applications, it is sufficient to estimate coarse head to infer gaze direction. Indeed for any application in which the camera is situated unobtrusively in an overhead corner, the only possible inference is coarse pose because of the limitations of the quality and resolution of the incoming data. However, the vast majority of research in head pose estimation deals with tracki...

Advertising agencies have a growing interest in finding out if roadside advertisements have reached the target audiences. The drivers’ head position’ would enable us to determine if they have been looking at the billboards. Numerous researches were focusing on the drivers’ attention from inside their cars; however, some have tried to determine the interaction between the drivers and outside obj...