Exploiting temporal context in vision-based navigation

Probabilistic relaxation has been used previously as the basis for the development of an algorithm to label features extracted from an image with corresponding features from a model. The algorithm can be executed in a deterministic manner, making it particularly appropriate for real-time methods. In this paper, we show how the method may be adapted to image sequences, taken from a moving camera, in order to provide navigation information. We show how knowledge of the camera motion can be incorporated into the labelling algorithm in order to provide better real-time performance and improved robustness.