Delayed Features Initialization for Inverse Depth Monocular SLAM

Recently, the unified inverse depth parametrization has shown to be a good option for challenging monocular SLAM problem, in a scheme of EKF for the estimation of the stochastic map and camera pose. In the original approach, features are initialized in the first frame observed (undelayed initialization), this aspect has advantages but also some problems. In this paper a delayed feature initialization is proposed for adding new features to the stochastic map. The results show that delayed initialization can improve some aspects without losing the performance and unified aspect of the original method, when initial reference points are used in order to fix a metric scale in the map.