Probabilistic Head Pose Tracking Evaluation in Single and Multiple Camera Setups

This paper presents our participation in the CLEAR 07 evaluation workshop head pose estimation tasks where two head pose estimation tasks were to be addressed. The first task estimates head poses with respect to (w.r.t.) a single camera capturing people seated in a meeting room scenario. The second task consisted of estimating the head pose of people moving in a room from four cameras w.r.t. a global room coordinate. To solve the first task, we used a probabilistic exemplar-based head pose tracking method using a mixed state particle filter based on a represention in a joint state space of head localization and pose variable. This state space representation allows the combined search for both the optimal head location and pose. To solve the second task, we first applied the same head tracking framework to estimate the head pose w.r.t each of the four camera. Then, using the camera calibration parameters, the head poses w.r.t. individual cameras were transformed into head poses w.r.t to the global room coordinates, and the measures obtained from the four cameras were fused using reliability measures based on skin detection. Good head pose tracking performances were obtained for both tasks

Unobtrusive and pervasive video-based eye-gaze tracking

Eye-gaze tracking has long been considered a desktop technology that finds its use inside the traditional office setting, where the operating conditions may be controlled. Nonetheless, recent advancements in mobile technology and a growing interest in capturing natural human behaviour have motivated an emerging interest in tracking eye movements within unconstrained real-life conditions, referred to as pervasive eye-gaze tracking. This critical review focuses on emerging passive and unobtrusive video-based eye-gaze tracking methods in recent literature, with the aim to identify different research avenues that are being followed in response to the challenges of pervasive eye-gaze tracking. Different eye-gaze tracking approaches are discussed in order to bring out their strengths and weaknesses, and to identify any limitations, within the context of pervasive eye-gaze tracking, that have yet to be considered by the computer vision community.peer-reviewe

Model-Based Environmental Visual Perception for Humanoid Robots

The visual perception of a robot should answer two fundamental questions: What? and Where? In order to properly and efficiently reply to these questions, it is essential to establish a bidirectional coupling between the external stimuli and the internal representations. This coupling links the physical world with the inner abstraction models by sensor transformation, recognition, matching and optimization algorithms. The objective of this PhD is to establish this sensor-model coupling