This paper presents a computer vision based head tracking system for augmented reality. A camera is attached to a head mounted display and used to track markers in the user's field of view. These markers are movable on a table and used as interface with virtual objects. Furthermore, they are used as landmarks to track the user's viewpoint and viewing direction by a homography based camera pose estimation algorithm. By integrating this computer vision tracker with a commercially available InterSense tracker, we take the advantages of the small jitter of the former one without losing the tracking speed of the later one. For static and slow head motion the system has less than 0.3mm RMS of position jitter and 0.165 degrees RMS of orientation jitter.

Colour is an important and useful feature for object tracking and recognition in computer vision. However, it has the difficulty that the colour of the object changes if the illuminant colour changes. But under known illuminant colour it becomes a robust feature. There are more and more computer vision applications tracking humans, for example in interfaces for human computer interaction or automatic camera men, where skin colour is an often-used feature. Hence, it would be of significant importance to know the illuminant colour in such applications. This paper proposes a novel method to estimate the current illuminant colour from skin colour observations. The method is based on a physical model of reflections, the assumption that illuminant colours are located close to the Planckian locus, and the knowledge about the camera parameters. The method is empirically tested using real images. The average estimation error of the correlated colour temperature is as small as 180 K. Applications are for example in colour-based tracking to adapt to changes in lighting and in visualisation to re-render image colours to their appearance under canonical viewing conditions.