Discerning Objects from Ground and Target Pose Estimation in ladar Data using Robust Statistics

In this paper we present a novel way to analyze LADAR images and model its data. Having an aerial LADAR image as data source, our aim is to extract a parametric description of the ground of our scenario in order to discern between the data samples that belong to the ground and those that belong to vehicles, objects or clutter. In the second part of this paper we estimate the pose of the interesting objects by building its corresponding oriented 3D bounding box. Our method uses robust statistics in order to extract proper descriptions of both the ground and the oriented bounding boxes of the objects. Specifically, we use two robust parameter estimators : The least median squares and the Helmolth tradeoff estimator, part of our prior work, depending on the percentage of outliers that may be present in the different steps of our approach.