Automatic tracking of flying vehicles using geodesic snakes and Kalman filtering

Abstract

This paper describes a tracking algorithm relying on active contours for target extraction and an extended Kalman filter for relative pose estimation. This work represents the first step towards treating the general problem for the control of several unmanned autonomous vehicles flying in formation using only local visual information. In particular, we only allow on-board passive sensing. The problem is an excellent paradigm for studying the use of visual information in a feedback loop, the central theme of controlled active vision.